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		<title>Neutronics in Fusion</title>
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		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[https://en.wikipedia.org/wiki/Neutron_transport Neutrons] generated in [https://en.wikipedia.org/wiki/Nuclear_fusion fusion reactions] carry most of the fusion energy and interact with surrounding materials &amp;lt;ref name=&amp;quot;NeutronTransport&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;NuclearFusion&amp;quot;/&amp;gt;. In fusion systems, especially deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are produced in large numbers. Their energy is deposited into surrounding materials through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which … tritium is continuously bred from lithium within the [[Breeding blanket]] to sustain reactor operation &amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following [[Plasma simulation]] and fast-ion modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in [[Tokamak]] and [[Stellarator]] plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://geant4.web.cern.ch Geant4]&lt;br /&gt;
| Detector and diagnostic modeling; energy deposition and shielding studies in complex 3D geometries &amp;lt;ref name=&amp;quot;Geant4&amp;quot;/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Neutron Detectors in Fusion Tokamaks ==&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Useful GitHub Repositories for Neutronics in Nuclear Fusion ==&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
== See Also ==&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
== External links ==&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Fusion Neutronics – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
* [https://www.tandfonline.com/doi/full/10.1080/15361055.2022.2141528 Advancing Methods for Fusion Neutronics: An Overview of Workflows and Nuclear Analysis Activities at UKAEA]&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-13-6520-1 Neutronics of Advanced Nuclear Systems]&lt;br /&gt;
* [https://doi.org/10.1016/S0920-3796(00)00160-5 Neutronics on inertial fusion reactors]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NeutronTransport&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Neutron transport,&amp;quot; Wikipedia, https://en.wikipedia.org/wiki/Neutron_transport&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NuclearFusion&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Nuclear fusion,&amp;quot; Wikipedia, https://en.wikipedia.org/wiki/Nuclear_fusion&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Geant4&amp;quot;&amp;gt;&lt;br /&gt;
S. Agostinelli et al., &amp;quot;GEANT4 — a simulation toolkit,&amp;quot; *Nuclear Instruments and Methods in Physics Research Section A*, vol. 506, pp. 250–303, 2003. https://doi.org/10.1016/S0168-9002(03)01368-8 &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
[[Category:Neutronics]]&lt;br /&gt;
[[Category:Software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8594</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8594"/>
		<updated>2026-03-29T17:41:13Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[https://en.wikipedia.org/wiki/Neutron_transport Neutrons] generated in [https://en.wikipedia.org/wiki/Nuclear_fusion fusion reactions] carry most of the fusion energy and interact with surrounding materials. In fusion systems, especially deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are produced in large numbers. Their energy is deposited into surrounding materials through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which … tritium is continuously bred from lithium within the [[Breeding blanket]] to sustain reactor operation &amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following [[Plasma simulation]] and fast-ion modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in [[Tokamak]] and [[Stellarator]] plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://geant4.web.cern.ch Geant4]&lt;br /&gt;
| Detector and diagnostic modeling; energy deposition and shielding studies in complex 3D geometries &amp;lt;ref name=&amp;quot;Geant4&amp;quot;/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Neutron Detectors in Fusion Tokamaks ==&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Useful GitHub Repositories for Neutronics in Nuclear Fusion ==&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
== See Also ==&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
== External links ==&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Fusion Neutronics – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
* [https://www.tandfonline.com/doi/full/10.1080/15361055.2022.2141528 Advancing Methods for Fusion Neutronics: An Overview of Workflows and Nuclear Analysis Activities at UKAEA]&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-13-6520-1 Neutronics of Advanced Nuclear Systems]&lt;br /&gt;
* [https://doi.org/10.1016/S0920-3796(00)00160-5 Neutronics on inertial fusion reactors]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Geant4&amp;quot;&amp;gt;&lt;br /&gt;
S. Agostinelli et al., &amp;quot;GEANT4 — a simulation toolkit,&amp;quot; *Nuclear Instruments and Methods in Physics Research Section A*, vol. 506, pp. 250–303, 2003. https://doi.org/10.1016/S0168-9002(03)01368-8 &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
[[Category:Neutronics]]&lt;br /&gt;
[[Category:Software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8593</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8593"/>
		<updated>2026-03-29T17:20:54Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* External links */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[https://en.wikipedia.org/wiki/Neutron_transport Neutron transport] in [https://en.wikipedia.org/wiki/Nuclear_fusion fusion] describes the behavior and interactions of neutrons produced during fusion reactions. In [[Nuclear fusion]] systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which … tritium is continuously bred from lithium within the [[Breeding blanket]] to sustain reactor operation &amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following [[Plasma simulation]] and fast-ion modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in [[Tokamak]] and [[Stellarator]] plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://geant4.web.cern.ch Geant4]&lt;br /&gt;
| Detector and diagnostic modeling; energy deposition and shielding studies in complex 3D geometries &amp;lt;ref name=&amp;quot;Geant4&amp;quot;/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Neutron Detectors in Fusion Tokamaks ==&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Useful GitHub Repositories for Neutronics in Nuclear Fusion ==&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
== See Also ==&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
== External links ==&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Fusion Neutronics – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
* [https://www.tandfonline.com/doi/full/10.1080/15361055.2022.2141528 Advancing Methods for Fusion Neutronics: An Overview of Workflows and Nuclear Analysis Activities at UKAEA]&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-13-6520-1 Neutronics of Advanced Nuclear Systems]&lt;br /&gt;
* [https://doi.org/10.1016/S0920-3796(00)00160-5 Neutronics on inertial fusion reactors]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Geant4&amp;quot;&amp;gt;&lt;br /&gt;
S. Agostinelli et al., &amp;quot;GEANT4 — a simulation toolkit,&amp;quot; *Nuclear Instruments and Methods in Physics Research Section A*, vol. 506, pp. 250–303, 2003. https://doi.org/10.1016/S0168-9002(03)01368-8 &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
[[Category:Neutronics]]&lt;br /&gt;
[[Category:Software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8573</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8573"/>
		<updated>2026-02-15T11:08:56Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* Neutron Interactions in Fusion Devices */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[https://en.wikipedia.org/wiki/Neutron_transport Neutron transport] in [https://en.wikipedia.org/wiki/Nuclear_fusion fusion] describes the behavior and interactions of neutrons produced during fusion reactions. In [[Nuclear fusion]] systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which … tritium is continuously bred from lithium within the [[Breeding blanket]] to sustain reactor operation &amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following [[Plasma simulation]] and fast-ion modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in [[Tokamak]] and [[Stellarator]] plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://geant4.web.cern.ch Geant4]&lt;br /&gt;
| Detector and diagnostic modeling; energy deposition and shielding studies in complex 3D geometries &amp;lt;ref name=&amp;quot;Geant4&amp;quot;/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Neutron Detectors in Fusion Tokamaks ==&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Useful GitHub Repositories for Neutronics in Nuclear Fusion ==&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
== See Also ==&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
== External links ==&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Geant4&amp;quot;&amp;gt;&lt;br /&gt;
S. Agostinelli et al., &amp;quot;GEANT4 — a simulation toolkit,&amp;quot; *Nuclear Instruments and Methods in Physics Research Section A*, vol. 506, pp. 250–303, 2003. https://doi.org/10.1016/S0168-9002(03)01368-8 &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
[[Category:Neutronics]]&lt;br /&gt;
[[Category:Software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8572</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8572"/>
		<updated>2026-02-15T11:05:23Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* Neutron Modeling in Plasma Codes */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[https://en.wikipedia.org/wiki/Neutron_transport Neutron transport] in [https://en.wikipedia.org/wiki/Nuclear_fusion fusion] describes the behavior and interactions of neutrons produced during fusion reactions. In [[Nuclear fusion]] systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following [[Plasma simulation]] and fast-ion modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in [[Tokamak]] and [[Stellarator]] plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://geant4.web.cern.ch Geant4]&lt;br /&gt;
| Detector and diagnostic modeling; energy deposition and shielding studies in complex 3D geometries &amp;lt;ref name=&amp;quot;Geant4&amp;quot;/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Neutron Detectors in Fusion Tokamaks ==&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Useful GitHub Repositories for Neutronics in Nuclear Fusion ==&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
== See Also ==&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
== External links ==&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Geant4&amp;quot;&amp;gt;&lt;br /&gt;
S. Agostinelli et al., &amp;quot;GEANT4 — a simulation toolkit,&amp;quot; *Nuclear Instruments and Methods in Physics Research Section A*, vol. 506, pp. 250–303, 2003. https://doi.org/10.1016/S0168-9002(03)01368-8 &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
[[Category:Neutronics]]&lt;br /&gt;
[[Category:Software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8571</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8571"/>
		<updated>2026-02-15T10:58:27Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[https://en.wikipedia.org/wiki/Neutron_transport Neutron transport] in [https://en.wikipedia.org/wiki/Nuclear_fusion fusion] describes the behavior and interactions of neutrons produced during fusion reactions. In [[Nuclear fusion]] systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in [[Tokamak]] and [[Stellarator]] plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://geant4.web.cern.ch Geant4]&lt;br /&gt;
| Detector and diagnostic modeling; energy deposition and shielding studies in complex 3D geometries &amp;lt;ref name=&amp;quot;Geant4&amp;quot;/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Neutron Detectors in Fusion Tokamaks ==&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Useful GitHub Repositories for Neutronics in Nuclear Fusion ==&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
== See Also ==&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
== External links ==&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Geant4&amp;quot;&amp;gt;&lt;br /&gt;
S. Agostinelli et al., &amp;quot;GEANT4 — a simulation toolkit,&amp;quot; *Nuclear Instruments and Methods in Physics Research Section A*, vol. 506, pp. 250–303, 2003. https://doi.org/10.1016/S0168-9002(03)01368-8 &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
[[Category:Neutronics]]&lt;br /&gt;
[[Category:Software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8570</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8570"/>
		<updated>2026-02-12T20:09:02Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* References */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[https://en.wikipedia.org/wiki/Neutron_transport Neutron transport] in [https://en.wikipedia.org/wiki/Nuclear_fusion fusion] describes the behavior and interactions of neutrons produced during fusion reactions. In [[Nuclear fusion]] systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://geant4.web.cern.ch Geant4]&lt;br /&gt;
| Detector and diagnostic modeling; energy deposition and shielding studies in complex 3D geometries &amp;lt;ref name=&amp;quot;Geant4&amp;quot;/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Geant4&amp;quot;&amp;gt;&lt;br /&gt;
S. Agostinelli et al., &amp;quot;GEANT4 — a simulation toolkit,&amp;quot; *Nuclear Instruments and Methods in Physics Research Section A*, vol. 506, pp. 250–303, 2003. https://doi.org/10.1016/S0168-9002(03)01368-8 &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
[[Category:Neutronics]]&lt;br /&gt;
[[Category:Software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Category:Neutronics&amp;diff=8568</id>
		<title>Category:Neutronics</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Category:Neutronics&amp;diff=8568"/>
		<updated>2026-02-11T08:10:55Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: Created page with &amp;quot;This category contains pages related to neutronics, neutron transport, and computational neutron analysis in fusion research.&amp;quot;&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;This category contains pages related to neutronics, neutron transport, and computational neutron analysis in fusion research.&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8567</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8567"/>
		<updated>2026-02-11T08:10:09Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[https://en.wikipedia.org/wiki/Neutron_transport Neutron transport] in [https://en.wikipedia.org/wiki/Nuclear_fusion fusion] describes the behavior and interactions of neutrons produced during fusion reactions. In [[Nuclear fusion]] systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://geant4.web.cern.ch Geant4]&lt;br /&gt;
| Detector and diagnostic modeling; energy deposition and shielding studies in complex 3D geometries &amp;lt;ref name=&amp;quot;Geant4&amp;quot;/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Geant4&amp;quot;&amp;gt;&lt;br /&gt;
S. Agostinelli et al., &amp;quot;GEANT4 — a simulation toolkit,&amp;quot; *Nuclear Instruments and Methods in Physics Research Section A*, vol. 506, pp. 250–303, 2003. https://doi.org/10.1016/S0168-9002(03)01368-8 &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
[[Category:Neutronics]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8566</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8566"/>
		<updated>2026-02-11T08:06:56Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[https://en.wikipedia.org/wiki/Neutron_transport Neutron transport] in [https://en.wikipedia.org/wiki/Nuclear_fusion fusion] describes the behavior and interactions of neutrons produced during fusion reactions. In [[Nuclear fusion]] systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://geant4.web.cern.ch Geant4]&lt;br /&gt;
| Detector and diagnostic modeling; energy deposition and shielding studies in complex 3D geometries &amp;lt;ref name=&amp;quot;Geant4&amp;quot;/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Geant4&amp;quot;&amp;gt;&lt;br /&gt;
S. Agostinelli et al., &amp;quot;GEANT4 — a simulation toolkit,&amp;quot; *Nuclear Instruments and Methods in Physics Research Section A*, vol. 506, pp. 250–303, 2003. https://doi.org/10.1016/S0168-9002(03)01368-8 &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
[[Category:Software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8565</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8565"/>
		<updated>2026-02-11T08:01:32Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* References */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[https://en.wikipedia.org/wiki/Neutron_transport Neutron transport] in [https://en.wikipedia.org/wiki/Nuclear_fusion fusion] describes the behavior and interactions of neutrons produced during fusion reactions. In [[Nuclear fusion]] systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://geant4.web.cern.ch Geant4]&lt;br /&gt;
| Detector and diagnostic modeling; energy deposition and shielding studies in complex 3D geometries &amp;lt;ref name=&amp;quot;Geant4&amp;quot;/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Geant4&amp;quot;&amp;gt;&lt;br /&gt;
S. Agostinelli et al., &amp;quot;GEANT4 — a simulation toolkit,&amp;quot; *Nuclear Instruments and Methods in Physics Research Section A*, vol. 506, pp. 250–303, 2003. https://doi.org/10.1016/S0168-9002(03)01368-8 &lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8564</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8564"/>
		<updated>2026-02-11T08:00:16Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* References */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[https://en.wikipedia.org/wiki/Neutron_transport Neutron transport] in [https://en.wikipedia.org/wiki/Nuclear_fusion fusion] describes the behavior and interactions of neutrons produced during fusion reactions. In [[Nuclear fusion]] systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://geant4.web.cern.ch Geant4]&lt;br /&gt;
| Detector and diagnostic modeling; energy deposition and shielding studies in complex 3D geometries &amp;lt;ref name=&amp;quot;Geant4&amp;quot;/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Geant4&amp;quot;&amp;gt;&lt;br /&gt;
S. Agostinelli et al., &amp;quot;GEANT4 — a simulation toolkit,&amp;quot; *Nuclear Instruments and Methods in Physics Research Section A*, vol. 506, pp. 250–303, 2003. https://doi.org/10.1016/S0168-9002(03)01368-8 :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8563</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8563"/>
		<updated>2026-02-11T07:57:36Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* Neutron Modeling Using Monte Carlo Neutronics Codes */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[https://en.wikipedia.org/wiki/Neutron_transport Neutron transport] in [https://en.wikipedia.org/wiki/Nuclear_fusion fusion] describes the behavior and interactions of neutrons produced during fusion reactions. In [[Nuclear fusion]] systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://geant4.web.cern.ch Geant4]&lt;br /&gt;
| Detector and diagnostic modeling; energy deposition and shielding studies in complex 3D geometries &amp;lt;ref name=&amp;quot;Geant4&amp;quot;/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8562</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8562"/>
		<updated>2026-02-11T07:53:55Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[https://en.wikipedia.org/wiki/Neutron_transport Neutron transport] in [https://en.wikipedia.org/wiki/Nuclear_fusion fusion] describes the behavior and interactions of neutrons produced during fusion reactions. In [[Nuclear fusion]] systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8561</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8561"/>
		<updated>2026-02-11T07:16:00Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* See Also */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8560</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8560"/>
		<updated>2026-02-11T07:13:14Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* See Also */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8556</id>
		<title>GENE</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8556"/>
		<updated>2026-02-09T22:19:27Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&#039;&#039;&#039;GENE&#039;&#039;&#039; (&#039;&#039;&#039;Gyrokinetic Electromagnetic Numerical Experiment&#039;&#039;&#039;) is an open-source computer simulation code used to study plasma turbulence in magnetic confinement fusion devices. GENE solves the gyrokinetic equations to simulate electromagnetic turbulence in plasmas, which is critical for understanding energy confinement in fusion reactors like tokamaks and stellarators.&lt;br /&gt;
&lt;br /&gt;
==Overview==&lt;br /&gt;
&lt;br /&gt;
[https://genecode.org/ GENE] is a gyrokinetic turbulence code that simulates plasma behavior at very small scales comparable to the ion and electron gyroradius. The code was originally developed at the [https://www.ipp.mpg.de/ Max Planck Institute for Plasma Physics] in Garching, Germany, with the first version written by [https://www.ipp.mpg.de/4159541/jenko Frank Jenko] in 1999.&amp;lt;ref&amp;gt;Jenko, F. (1999). &amp;quot;Development of GENE code&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/5295353/06_22&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
GENE is widely used in the international fusion research community and is considered one of the leading codes for plasma turbulence simulations. The code has been continuously developed by an international team of researchers and is designed to run on high-performance supercomputers.&lt;br /&gt;
&lt;br /&gt;
[[File:GENE_image.jpg|thumb|right|350px|D–T The GENE code. Source: &#039;&#039;Gyrokinetic Electromagnetic Numerical Experiment&#039;&#039;, [https://genecode.org/]]]&lt;br /&gt;
&lt;br /&gt;
===Purpose and Applications===&lt;br /&gt;
&lt;br /&gt;
The main purpose of GENE is to understand and predict turbulent transport in fusion plasmas. Plasma turbulence is one of the key factors limiting energy confinement in magnetic fusion devices, which directly affects the performance and efficiency of potential fusion power plants. By simulating this turbulence, GENE helps researchers:&lt;br /&gt;
&lt;br /&gt;
* Predict energy confinement times in fusion experiments&lt;br /&gt;
* Understand heat and particle transport mechanisms&lt;br /&gt;
* Optimize plasma conditions for better performance&lt;br /&gt;
* Design future fusion devices including ITER&lt;br /&gt;
* Validate theoretical models against experimental data&lt;br /&gt;
&lt;br /&gt;
The code has been successfully validated against experimental measurements from major fusion devices including ASDEX Upgrade and has shown excellent agreement with multiple simultaneous plasma observables.&lt;br /&gt;
&lt;br /&gt;
==Physical Model==&lt;br /&gt;
&lt;br /&gt;
GENE is based on gyrokinetic theory, which describes plasma behavior on spatial scales comparable to particle gyroradii and on time scales much slower than the cyclotron frequency. This approach reduces the complexity of the full kinetic description while retaining the essential physics of plasma turbulence.&lt;br /&gt;
&lt;br /&gt;
===Gyrokinetic Equations===&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic model assumes that:&lt;br /&gt;
* The plasma is strongly magnetized&lt;br /&gt;
* Perpendicular spatial scales are comparable to the ion gyroradius&lt;br /&gt;
* Frequencies are much lower than the ion cyclotron frequency&lt;br /&gt;
* Perturbations are small compared to background quantities&lt;br /&gt;
&lt;br /&gt;
The fundamental equations solved by GENE include:&lt;br /&gt;
&lt;br /&gt;
====Gyrokinetic Vlasov Equation====&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic equation describes the evolution of the perturbed distribution function. In simplified form, it can be written as:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\frac{\partial h_s}{\partial t} + \mathbf{v}_{\text{gc}} \cdot \nabla h_s + \dot{v}_\parallel \frac{\partial h_s}{\partial v_\parallel} = C(h_s)&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
where:&lt;br /&gt;
* &amp;lt;math&amp;gt;h_s&amp;lt;/math&amp;gt; is the perturbed distribution function for species &#039;&#039;s&#039;&#039;&lt;br /&gt;
* &amp;lt;math&amp;gt;\mathbf{v}_{\text{gc}}&amp;lt;/math&amp;gt; is the guiding center velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;v_\parallel&amp;lt;/math&amp;gt; is the parallel velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;C(h_s)&amp;lt;/math&amp;gt; represents collisional effects&lt;br /&gt;
&lt;br /&gt;
====Maxwell&#039;s Equations====&lt;br /&gt;
&lt;br /&gt;
GENE couples the gyrokinetic equation to Maxwell&#039;s equations to determine the electromagnetic fields. In the electrostatic approximation, this reduces to the quasineutrality condition:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\sum_s Z_s e B \int dv_\parallel \, d\mu \, d\varphi \, h_s(\mathbf{R}) = \sum_s \frac{Z_s^2 e^2 n_s \phi}{T_s}&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
For electromagnetic simulations, GENE also solves Ampère&#039;s law for the parallel magnetic field perturbations.&lt;br /&gt;
&lt;br /&gt;
===Turbulence Mechanisms===&lt;br /&gt;
&lt;br /&gt;
GENE can simulate various types of plasma turbulence, including:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Ion Temperature Gradient (ITG) modes&#039;&#039;&#039; - driven by temperature gradients in the plasma&lt;br /&gt;
* &#039;&#039;&#039;Trapped Electron Modes (TEM)&#039;&#039;&#039; - caused by particles trapped in magnetic field variations&lt;br /&gt;
* &#039;&#039;&#039;Electron Temperature Gradient (ETG) modes&#039;&#039;&#039; - electron-scale turbulence&lt;br /&gt;
* &#039;&#039;&#039;Kinetic Ballooning Modes (KBM)&#039;&#039;&#039; - pressure-driven instabilities&lt;br /&gt;
* &#039;&#039;&#039;Microtearing modes&#039;&#039;&#039; - electromagnetic instabilities that can tear magnetic field lines&lt;br /&gt;
&lt;br /&gt;
==Numerical Methods==&lt;br /&gt;
&lt;br /&gt;
GENE is a Eulerian code, meaning it solves the gyrokinetic equations on a fixed grid in phase space rather than following individual particles. This approach has several advantages for turbulence simulations.&lt;br /&gt;
&lt;br /&gt;
===Discretization===&lt;br /&gt;
&lt;br /&gt;
The code uses a combination of numerical methods:&lt;br /&gt;
* &#039;&#039;&#039;Spectral methods&#039;&#039;&#039; in the perpendicular directions (for periodic boundary conditions)&lt;br /&gt;
* &#039;&#039;&#039;Finite differences&#039;&#039;&#039; in the radial direction (for global simulations)&lt;br /&gt;
* &#039;&#039;&#039;Upwind schemes&#039;&#039;&#039; along magnetic field lines&lt;br /&gt;
* &#039;&#039;&#039;Runge-Kutta methods&#039;&#039;&#039; for time integration&lt;br /&gt;
&lt;br /&gt;
===Coordinate Systems===&lt;br /&gt;
&lt;br /&gt;
GENE employs field-aligned coordinates that follow magnetic field lines, which is natural for strongly magnetized plasmas. Different versions of the code use different coordinate approaches:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Standard GENE&#039;&#039;&#039; - uses flux-tube or radially global geometry in tokamaks&lt;br /&gt;
* &#039;&#039;&#039;GENE-3D&#039;&#039;&#039; - full three-dimensional geometry for stellarators&lt;br /&gt;
* &#039;&#039;&#039;GENE-X&#039;&#039;&#039; - flux-coordinate independent (FCI) approach for edge and scrape-off layer regions&lt;br /&gt;
&lt;br /&gt;
==Code Versions and Extensions==&lt;br /&gt;
&lt;br /&gt;
===Local and Global Versions===&lt;br /&gt;
&lt;br /&gt;
GENE can operate in different spatial modes:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Local (flux-tube)&#039;&#039;&#039; - simulates a small radial region with periodic boundary conditions; computationally efficient for core turbulence&lt;br /&gt;
* &#039;&#039;&#039;Radially global&#039;&#039;&#039; - includes variations across the plasma radius; necessary for edge effects and profile evolution&lt;br /&gt;
&lt;br /&gt;
===GENE-3D===&lt;br /&gt;
&lt;br /&gt;
GENE-3D is an extension that handles the complex three-dimensional geometry of stellarators. Development of GENE-3D took approximately five years and was presented by Maurice Maurer and colleagues.&amp;lt;ref&amp;gt;Maurer, M. et al. &amp;quot;Promising computer simulations for stellarator plasmas&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/4928395/05_20&amp;lt;/ref&amp;gt; Unlike the original tokamak-oriented version, GENE-3D can simulate the full ion and electron dynamics in the complex magnetic field geometry of stellarators like Wendelstein 7-X.&lt;br /&gt;
&lt;br /&gt;
===GENE-X===&lt;br /&gt;
&lt;br /&gt;
GENE-X is a full-f gyrokinetic continuum code based on the flux-coordinate independent (FCI) approach.&amp;lt;ref&amp;gt;&amp;quot;GENE-X: A full-f gyrokinetic turbulence code based on the flux-coordinate independent approach&amp;quot; (2021). Computer Physics Communications. https://www.sciencedirect.com/science/article/abs/pii/S0010465521000989&amp;lt;/ref&amp;gt; This version was developed specifically to handle:&lt;br /&gt;
&lt;br /&gt;
* Edge and scrape-off layer turbulence&lt;br /&gt;
* Regions with magnetic X-points (where traditional field-aligned coordinates have singularities)&lt;br /&gt;
* Geometries without well-defined flux surfaces&lt;br /&gt;
* Transition regions between core and edge plasma&lt;br /&gt;
&lt;br /&gt;
GENE-X uses unstructured, locally Cartesian grids that provide flexibility while maintaining computational efficiency. The code is capable of simulating regions from the magnetic axis, across the separatrix, and into the scrape-off layer.&lt;br /&gt;
&lt;br /&gt;
==Development and Community==&lt;br /&gt;
&lt;br /&gt;
===History===&lt;br /&gt;
&lt;br /&gt;
Frank Jenko wrote the first version of GENE in 1999 during his early postdoctoral work.&amp;lt;ref&amp;gt;Jenko, F. (1999). &amp;quot;Development of GENE code&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/5295353/06_22&amp;lt;/ref&amp;gt; Since then, the code has been continuously developed and improved by an international team of researchers. Major development centers include:&lt;br /&gt;
&lt;br /&gt;
* Max Planck Institute for Plasma Physics (IPP), Garching, Germany&lt;br /&gt;
* Max Planck Computing and Data Facility (MPCDF), Germany&lt;br /&gt;
* Technical University of Munich, Germany&lt;br /&gt;
* University of Texas at Austin, USA&lt;br /&gt;
* École Polytechnique Fédérale de Lausanne (EPFL), Switzerland&lt;br /&gt;
* Many other international institutions&lt;br /&gt;
&lt;br /&gt;
===International Collaboration===&lt;br /&gt;
&lt;br /&gt;
The GENE Development Team is an international collaboration that includes members from universities and research laboratories across the world. The project welcomes contributions from the global fusion community and maintains an open-source development model.&lt;br /&gt;
&lt;br /&gt;
Institutions using GENE include research centers in Germany, USA, Switzerland, France, UK, Netherlands, Italy, Japan, India, China, South Korea, and many others.&lt;br /&gt;
&lt;br /&gt;
===High-Performance Computing===&lt;br /&gt;
&lt;br /&gt;
GENE has been at the forefront of high-performance computing in plasma physics since the 1960s. The code is designed to run efficiently on the world&#039;s largest supercomputers. In 2022, a major project was launched with €2.14 million in EU funding to develop an exascale version of GENE, pioneering the transition to exascale supercomputers.&amp;lt;ref&amp;gt;&amp;quot;Nuclear fusion simulation to pioneer transition to exascale supercomputers&amp;quot; (2023). EUROfusion. Retrieved from https://euro-fusion.org/member-news/nuclear-fusion-simulation-to-pioneer-transition-to-exascale-supercomputers/&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
The goal is to create &amp;quot;digital twins&amp;quot; of fusion experiments like ITER, allowing researchers to predict plasma behavior rather than just interpret experimental results.&lt;br /&gt;
&lt;br /&gt;
==Validation and Impact==&lt;br /&gt;
&lt;br /&gt;
GENE has been extensively validated against experimental measurements from major fusion devices. A landmark 2025 study demonstrated successful multi-channel validation of GENE against ASDEX Upgrade tokamak data, comparing simultaneous measurements of multiple plasma properties including turbulence amplitudes, wavenumber spectra, and cross phases.&amp;lt;ref&amp;gt;&amp;quot;Milestone in predicting core plasma turbulence: successful multi-channel validation of the gyrokinetic code GENE&amp;quot; (2025). Nature Communications. https://www.nature.com/articles/s41467-025-56997-2&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
The code has been used to:&lt;br /&gt;
* Explain turbulence suppression by fast ions in tokamak plasmas&lt;br /&gt;
* Predict similar effects in stellarators&lt;br /&gt;
* Understand energy confinement scaling&lt;br /&gt;
* Design optimal plasma scenarios for ITER&lt;br /&gt;
* Investigate the effects of different wall materials (like tungsten) on plasma performance&lt;br /&gt;
&lt;br /&gt;
==See also==&lt;br /&gt;
&lt;br /&gt;
* [[Gyrokinetic simulations]]&lt;br /&gt;
* [[Plasma Physics at the LNF]]&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Tokamak]]&lt;br /&gt;
* [[Stellarator]]&lt;br /&gt;
* [[ITER]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
* [[MHD equilibrium]]&lt;br /&gt;
&lt;br /&gt;
==References==&lt;br /&gt;
&lt;br /&gt;
&amp;lt;references/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
==External links==&lt;br /&gt;
&lt;br /&gt;
* [https://genecode.org Official GENE website]&lt;br /&gt;
* [https://www.ipp.mpg.de Max Planck Institute for Plasma Physics]&lt;br /&gt;
* [https://genecode.org/license.html GENE license &amp;amp; how to obtain the source]&lt;br /&gt;
* [https://www.iter.org ITER Organization]&lt;br /&gt;
&lt;br /&gt;
[[Category:Software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=File:GENE_image.jpg&amp;diff=8555</id>
		<title>File:GENE image.jpg</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=File:GENE_image.jpg&amp;diff=8555"/>
		<updated>2026-02-09T22:13:32Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8554</id>
		<title>GENE</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8554"/>
		<updated>2026-02-09T22:10:14Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&#039;&#039;&#039;GENE&#039;&#039;&#039; (&#039;&#039;&#039;Gyrokinetic Electromagnetic Numerical Experiment&#039;&#039;&#039;) is an open-source computer simulation code used to study plasma turbulence in magnetic confinement fusion devices. GENE solves the gyrokinetic equations to simulate electromagnetic turbulence in plasmas, which is critical for understanding energy confinement in fusion reactors like tokamaks and stellarators.&lt;br /&gt;
&lt;br /&gt;
==Overview==&lt;br /&gt;
&lt;br /&gt;
[https://genecode.org/ GENE] is a gyrokinetic turbulence code that simulates plasma behavior at very small scales comparable to the ion and electron gyroradius. The code was originally developed at the [https://www.ipp.mpg.de/ Max Planck Institute for Plasma Physics] in Garching, Germany, with the first version written by [https://www.ipp.mpg.de/4159541/jenko Frank Jenko] in 1999.&amp;lt;ref&amp;gt;Jenko, F. (1999). &amp;quot;Development of GENE code&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/5295353/06_22&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
GENE is widely used in the international fusion research community and is considered one of the leading codes for plasma turbulence simulations. The code has been continuously developed by an international team of researchers and is designed to run on high-performance supercomputers.&lt;br /&gt;
&lt;br /&gt;
===Purpose and Applications===&lt;br /&gt;
&lt;br /&gt;
The main purpose of GENE is to understand and predict turbulent transport in fusion plasmas. Plasma turbulence is one of the key factors limiting energy confinement in magnetic fusion devices, which directly affects the performance and efficiency of potential fusion power plants. By simulating this turbulence, GENE helps researchers:&lt;br /&gt;
&lt;br /&gt;
* Predict energy confinement times in fusion experiments&lt;br /&gt;
* Understand heat and particle transport mechanisms&lt;br /&gt;
* Optimize plasma conditions for better performance&lt;br /&gt;
* Design future fusion devices including ITER&lt;br /&gt;
* Validate theoretical models against experimental data&lt;br /&gt;
&lt;br /&gt;
The code has been successfully validated against experimental measurements from major fusion devices including ASDEX Upgrade and has shown excellent agreement with multiple simultaneous plasma observables.&lt;br /&gt;
&lt;br /&gt;
==Physical Model==&lt;br /&gt;
&lt;br /&gt;
GENE is based on gyrokinetic theory, which describes plasma behavior on spatial scales comparable to particle gyroradii and on time scales much slower than the cyclotron frequency. This approach reduces the complexity of the full kinetic description while retaining the essential physics of plasma turbulence.&lt;br /&gt;
&lt;br /&gt;
===Gyrokinetic Equations===&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic model assumes that:&lt;br /&gt;
* The plasma is strongly magnetized&lt;br /&gt;
* Perpendicular spatial scales are comparable to the ion gyroradius&lt;br /&gt;
* Frequencies are much lower than the ion cyclotron frequency&lt;br /&gt;
* Perturbations are small compared to background quantities&lt;br /&gt;
&lt;br /&gt;
The fundamental equations solved by GENE include:&lt;br /&gt;
&lt;br /&gt;
====Gyrokinetic Vlasov Equation====&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic equation describes the evolution of the perturbed distribution function. In simplified form, it can be written as:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\frac{\partial h_s}{\partial t} + \mathbf{v}_{\text{gc}} \cdot \nabla h_s + \dot{v}_\parallel \frac{\partial h_s}{\partial v_\parallel} = C(h_s)&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
where:&lt;br /&gt;
* &amp;lt;math&amp;gt;h_s&amp;lt;/math&amp;gt; is the perturbed distribution function for species &#039;&#039;s&#039;&#039;&lt;br /&gt;
* &amp;lt;math&amp;gt;\mathbf{v}_{\text{gc}}&amp;lt;/math&amp;gt; is the guiding center velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;v_\parallel&amp;lt;/math&amp;gt; is the parallel velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;C(h_s)&amp;lt;/math&amp;gt; represents collisional effects&lt;br /&gt;
&lt;br /&gt;
====Maxwell&#039;s Equations====&lt;br /&gt;
&lt;br /&gt;
GENE couples the gyrokinetic equation to Maxwell&#039;s equations to determine the electromagnetic fields. In the electrostatic approximation, this reduces to the quasineutrality condition:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\sum_s Z_s e B \int dv_\parallel \, d\mu \, d\varphi \, h_s(\mathbf{R}) = \sum_s \frac{Z_s^2 e^2 n_s \phi}{T_s}&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
For electromagnetic simulations, GENE also solves Ampère&#039;s law for the parallel magnetic field perturbations.&lt;br /&gt;
&lt;br /&gt;
===Turbulence Mechanisms===&lt;br /&gt;
&lt;br /&gt;
GENE can simulate various types of plasma turbulence, including:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Ion Temperature Gradient (ITG) modes&#039;&#039;&#039; - driven by temperature gradients in the plasma&lt;br /&gt;
* &#039;&#039;&#039;Trapped Electron Modes (TEM)&#039;&#039;&#039; - caused by particles trapped in magnetic field variations&lt;br /&gt;
* &#039;&#039;&#039;Electron Temperature Gradient (ETG) modes&#039;&#039;&#039; - electron-scale turbulence&lt;br /&gt;
* &#039;&#039;&#039;Kinetic Ballooning Modes (KBM)&#039;&#039;&#039; - pressure-driven instabilities&lt;br /&gt;
* &#039;&#039;&#039;Microtearing modes&#039;&#039;&#039; - electromagnetic instabilities that can tear magnetic field lines&lt;br /&gt;
&lt;br /&gt;
==Numerical Methods==&lt;br /&gt;
&lt;br /&gt;
GENE is a Eulerian code, meaning it solves the gyrokinetic equations on a fixed grid in phase space rather than following individual particles. This approach has several advantages for turbulence simulations.&lt;br /&gt;
&lt;br /&gt;
===Discretization===&lt;br /&gt;
&lt;br /&gt;
The code uses a combination of numerical methods:&lt;br /&gt;
* &#039;&#039;&#039;Spectral methods&#039;&#039;&#039; in the perpendicular directions (for periodic boundary conditions)&lt;br /&gt;
* &#039;&#039;&#039;Finite differences&#039;&#039;&#039; in the radial direction (for global simulations)&lt;br /&gt;
* &#039;&#039;&#039;Upwind schemes&#039;&#039;&#039; along magnetic field lines&lt;br /&gt;
* &#039;&#039;&#039;Runge-Kutta methods&#039;&#039;&#039; for time integration&lt;br /&gt;
&lt;br /&gt;
===Coordinate Systems===&lt;br /&gt;
&lt;br /&gt;
GENE employs field-aligned coordinates that follow magnetic field lines, which is natural for strongly magnetized plasmas. Different versions of the code use different coordinate approaches:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Standard GENE&#039;&#039;&#039; - uses flux-tube or radially global geometry in tokamaks&lt;br /&gt;
* &#039;&#039;&#039;GENE-3D&#039;&#039;&#039; - full three-dimensional geometry for stellarators&lt;br /&gt;
* &#039;&#039;&#039;GENE-X&#039;&#039;&#039; - flux-coordinate independent (FCI) approach for edge and scrape-off layer regions&lt;br /&gt;
&lt;br /&gt;
==Code Versions and Extensions==&lt;br /&gt;
&lt;br /&gt;
===Local and Global Versions===&lt;br /&gt;
&lt;br /&gt;
GENE can operate in different spatial modes:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Local (flux-tube)&#039;&#039;&#039; - simulates a small radial region with periodic boundary conditions; computationally efficient for core turbulence&lt;br /&gt;
* &#039;&#039;&#039;Radially global&#039;&#039;&#039; - includes variations across the plasma radius; necessary for edge effects and profile evolution&lt;br /&gt;
&lt;br /&gt;
===GENE-3D===&lt;br /&gt;
&lt;br /&gt;
GENE-3D is an extension that handles the complex three-dimensional geometry of stellarators. Development of GENE-3D took approximately five years and was presented by Maurice Maurer and colleagues.&amp;lt;ref&amp;gt;Maurer, M. et al. &amp;quot;Promising computer simulations for stellarator plasmas&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/4928395/05_20&amp;lt;/ref&amp;gt; Unlike the original tokamak-oriented version, GENE-3D can simulate the full ion and electron dynamics in the complex magnetic field geometry of stellarators like Wendelstein 7-X.&lt;br /&gt;
&lt;br /&gt;
===GENE-X===&lt;br /&gt;
&lt;br /&gt;
GENE-X is a full-f gyrokinetic continuum code based on the flux-coordinate independent (FCI) approach.&amp;lt;ref&amp;gt;&amp;quot;GENE-X: A full-f gyrokinetic turbulence code based on the flux-coordinate independent approach&amp;quot; (2021). Computer Physics Communications. https://www.sciencedirect.com/science/article/abs/pii/S0010465521000989&amp;lt;/ref&amp;gt; This version was developed specifically to handle:&lt;br /&gt;
&lt;br /&gt;
* Edge and scrape-off layer turbulence&lt;br /&gt;
* Regions with magnetic X-points (where traditional field-aligned coordinates have singularities)&lt;br /&gt;
* Geometries without well-defined flux surfaces&lt;br /&gt;
* Transition regions between core and edge plasma&lt;br /&gt;
&lt;br /&gt;
GENE-X uses unstructured, locally Cartesian grids that provide flexibility while maintaining computational efficiency. The code is capable of simulating regions from the magnetic axis, across the separatrix, and into the scrape-off layer.&lt;br /&gt;
&lt;br /&gt;
==Development and Community==&lt;br /&gt;
&lt;br /&gt;
===History===&lt;br /&gt;
&lt;br /&gt;
Frank Jenko wrote the first version of GENE in 1999 during his early postdoctoral work.&amp;lt;ref&amp;gt;Jenko, F. (1999). &amp;quot;Development of GENE code&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/5295353/06_22&amp;lt;/ref&amp;gt; Since then, the code has been continuously developed and improved by an international team of researchers. Major development centers include:&lt;br /&gt;
&lt;br /&gt;
* Max Planck Institute for Plasma Physics (IPP), Garching, Germany&lt;br /&gt;
* Max Planck Computing and Data Facility (MPCDF), Germany&lt;br /&gt;
* Technical University of Munich, Germany&lt;br /&gt;
* University of Texas at Austin, USA&lt;br /&gt;
* École Polytechnique Fédérale de Lausanne (EPFL), Switzerland&lt;br /&gt;
* Many other international institutions&lt;br /&gt;
&lt;br /&gt;
===International Collaboration===&lt;br /&gt;
&lt;br /&gt;
The GENE Development Team is an international collaboration that includes members from universities and research laboratories across the world. The project welcomes contributions from the global fusion community and maintains an open-source development model.&lt;br /&gt;
&lt;br /&gt;
Institutions using GENE include research centers in Germany, USA, Switzerland, France, UK, Netherlands, Italy, Japan, India, China, South Korea, and many others.&lt;br /&gt;
&lt;br /&gt;
===High-Performance Computing===&lt;br /&gt;
&lt;br /&gt;
GENE has been at the forefront of high-performance computing in plasma physics since the 1960s. The code is designed to run efficiently on the world&#039;s largest supercomputers. In 2022, a major project was launched with €2.14 million in EU funding to develop an exascale version of GENE, pioneering the transition to exascale supercomputers.&amp;lt;ref&amp;gt;&amp;quot;Nuclear fusion simulation to pioneer transition to exascale supercomputers&amp;quot; (2023). EUROfusion. Retrieved from https://euro-fusion.org/member-news/nuclear-fusion-simulation-to-pioneer-transition-to-exascale-supercomputers/&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
The goal is to create &amp;quot;digital twins&amp;quot; of fusion experiments like ITER, allowing researchers to predict plasma behavior rather than just interpret experimental results.&lt;br /&gt;
&lt;br /&gt;
==Validation and Impact==&lt;br /&gt;
&lt;br /&gt;
GENE has been extensively validated against experimental measurements from major fusion devices. A landmark 2025 study demonstrated successful multi-channel validation of GENE against ASDEX Upgrade tokamak data, comparing simultaneous measurements of multiple plasma properties including turbulence amplitudes, wavenumber spectra, and cross phases.&amp;lt;ref&amp;gt;&amp;quot;Milestone in predicting core plasma turbulence: successful multi-channel validation of the gyrokinetic code GENE&amp;quot; (2025). Nature Communications. https://www.nature.com/articles/s41467-025-56997-2&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
The code has been used to:&lt;br /&gt;
* Explain turbulence suppression by fast ions in tokamak plasmas&lt;br /&gt;
* Predict similar effects in stellarators&lt;br /&gt;
* Understand energy confinement scaling&lt;br /&gt;
* Design optimal plasma scenarios for ITER&lt;br /&gt;
* Investigate the effects of different wall materials (like tungsten) on plasma performance&lt;br /&gt;
&lt;br /&gt;
==See also==&lt;br /&gt;
&lt;br /&gt;
* [[Gyrokinetic simulations]]&lt;br /&gt;
* [[Plasma Physics at the LNF]]&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Tokamak]]&lt;br /&gt;
* [[Stellarator]]&lt;br /&gt;
* [[ITER]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
* [[MHD equilibrium]]&lt;br /&gt;
&lt;br /&gt;
==References==&lt;br /&gt;
&lt;br /&gt;
&amp;lt;references/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
==External links==&lt;br /&gt;
&lt;br /&gt;
* [https://genecode.org Official GENE website]&lt;br /&gt;
* [https://www.ipp.mpg.de Max Planck Institute for Plasma Physics]&lt;br /&gt;
* [https://genecode.org/license.html GENE license &amp;amp; how to obtain the source]&lt;br /&gt;
* [https://www.iter.org ITER Organization]&lt;br /&gt;
&lt;br /&gt;
[[Category:Software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8553</id>
		<title>GENE</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8553"/>
		<updated>2026-02-09T22:06:00Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* External links */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&#039;&#039;&#039;GENE&#039;&#039;&#039; (&#039;&#039;&#039;Gyrokinetic Electromagnetic Numerical Experiment&#039;&#039;&#039;) is an open-source computer simulation code used to study plasma turbulence in magnetic confinement fusion devices. GENE solves the gyrokinetic equations to simulate electromagnetic turbulence in plasmas, which is critical for understanding energy confinement in fusion reactors like tokamaks and stellarators.&lt;br /&gt;
&lt;br /&gt;
==Overview==&lt;br /&gt;
&lt;br /&gt;
[https://genecode.org/ GENE] is a gyrokinetic turbulence code that simulates plasma behavior at very small scales comparable to the ion and electron gyroradius. The code was originally developed at the [https://www.ipp.mpg.de/ Max Planck Institute for Plasma Physics] in Garching, Germany, with the first version written by [https://www.ipp.mpg.de/4159541/jenko Frank Jenko] in 1999 [1].&lt;br /&gt;
&lt;br /&gt;
GENE is widely used in the international fusion research community and is considered one of the leading codes for plasma turbulence simulations. The code has been continuously developed by an international team of researchers and is designed to run on high-performance supercomputers.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Purpose and Applications===&lt;br /&gt;
&lt;br /&gt;
The main purpose of GENE is to understand and predict turbulent transport in fusion plasmas. Plasma turbulence is one of the key factors limiting energy confinement in magnetic fusion devices, which directly affects the performance and efficiency of potential fusion power plants. By simulating this turbulence, GENE helps researchers:&lt;br /&gt;
&lt;br /&gt;
* Predict energy confinement times in fusion experiments&lt;br /&gt;
* Understand heat and particle transport mechanisms&lt;br /&gt;
* Optimize plasma conditions for better performance&lt;br /&gt;
* Design future fusion devices including ITER&lt;br /&gt;
* Validate theoretical models against experimental data&lt;br /&gt;
&lt;br /&gt;
The code has been successfully validated against experimental measurements from major fusion devices including ASDEX Upgrade and has shown excellent agreement with multiple simultaneous plasma observables.&lt;br /&gt;
&lt;br /&gt;
==Physical Model==&lt;br /&gt;
&lt;br /&gt;
GENE is based on gyrokinetic theory, which describes plasma behavior on spatial scales comparable to particle gyroradii and on time scales much slower than the cyclotron frequency. This approach reduces the complexity of the full kinetic description while retaining the essential physics of plasma turbulence.&lt;br /&gt;
&lt;br /&gt;
===Gyrokinetic Equations===&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic model assumes that:&lt;br /&gt;
* The plasma is strongly magnetized&lt;br /&gt;
* Perpendicular spatial scales are comparable to the ion gyroradius&lt;br /&gt;
* Frequencies are much lower than the ion cyclotron frequency&lt;br /&gt;
* Perturbations are small compared to background quantities&lt;br /&gt;
&lt;br /&gt;
The fundamental equations solved by GENE include:&lt;br /&gt;
&lt;br /&gt;
====Gyrokinetic Vlasov Equation====&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic equation describes the evolution of the perturbed distribution function. In simplified form, it can be written as:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\frac{\partial h_s}{\partial t} + \mathbf{v}_{\text{gc}} \cdot \nabla h_s + \dot{v}_\parallel \frac{\partial h_s}{\partial v_\parallel} = C(h_s)&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
where:&lt;br /&gt;
* &amp;lt;math&amp;gt;h_s&amp;lt;/math&amp;gt; is the perturbed distribution function for species &#039;&#039;s&#039;&#039;&lt;br /&gt;
* &amp;lt;math&amp;gt;\mathbf{v}_{\text{gc}}&amp;lt;/math&amp;gt; is the guiding center velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;v_\parallel&amp;lt;/math&amp;gt; is the parallel velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;C(h_s)&amp;lt;/math&amp;gt; represents collisional effects&lt;br /&gt;
&lt;br /&gt;
====Maxwell&#039;s Equations====&lt;br /&gt;
&lt;br /&gt;
GENE couples the gyrokinetic equation to Maxwell&#039;s equations to determine the electromagnetic fields. In the electrostatic approximation, this reduces to the quasineutrality condition:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\sum_s Z_s e B \int dv_\parallel \, d\mu \, d\varphi \, h_s(\mathbf{R}) = \sum_s \frac{Z_s^2 e^2 n_s \phi}{T_s}&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
For electromagnetic simulations, GENE also solves Ampère&#039;s law for the parallel magnetic field perturbations.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Turbulence Mechanisms===&lt;br /&gt;
&lt;br /&gt;
GENE can simulate various types of plasma turbulence, including:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Ion Temperature Gradient (ITG) modes&#039;&#039;&#039; - driven by temperature gradients in the plasma&lt;br /&gt;
* &#039;&#039;&#039;Trapped Electron Modes (TEM)&#039;&#039;&#039; - caused by particles trapped in magnetic field variations&lt;br /&gt;
* &#039;&#039;&#039;Electron Temperature Gradient (ETG) modes&#039;&#039;&#039; - electron-scale turbulence&lt;br /&gt;
* &#039;&#039;&#039;Kinetic Ballooning Modes (KBM)&#039;&#039;&#039; - pressure-driven instabilities&lt;br /&gt;
* &#039;&#039;&#039;Microtearing modes&#039;&#039;&#039; - electromagnetic instabilities that can tear magnetic field lines&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Numerical Methods==&lt;br /&gt;
&lt;br /&gt;
GENE is a Eulerian code, meaning it solves the gyrokinetic equations on a fixed grid in phase space rather than following individual particles. This approach has several advantages for turbulence simulations.&lt;br /&gt;
&lt;br /&gt;
===Discretization===&lt;br /&gt;
&lt;br /&gt;
The code uses a combination of numerical methods:&lt;br /&gt;
* &#039;&#039;&#039;Spectral methods&#039;&#039;&#039; in the perpendicular directions (for periodic boundary conditions)&lt;br /&gt;
* &#039;&#039;&#039;Finite differences&#039;&#039;&#039; in the radial direction (for global simulations)&lt;br /&gt;
* &#039;&#039;&#039;Upwind schemes&#039;&#039;&#039; along magnetic field lines&lt;br /&gt;
* &#039;&#039;&#039;Runge-Kutta methods&#039;&#039;&#039; for time integration&lt;br /&gt;
&lt;br /&gt;
===Coordinate Systems===&lt;br /&gt;
&lt;br /&gt;
GENE employs field-aligned coordinates that follow magnetic field lines, which is natural for strongly magnetized plasmas. Different versions of the code use different coordinate approaches:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Standard GENE&#039;&#039;&#039; - uses flux-tube or radially global geometry in tokamaks&lt;br /&gt;
* &#039;&#039;&#039;GENE-3D&#039;&#039;&#039; - full three-dimensional geometry for stellarators&lt;br /&gt;
* &#039;&#039;&#039;GENE-X&#039;&#039;&#039; - flux-coordinate independent (FCI) approach for edge and scrape-off layer regions&lt;br /&gt;
&lt;br /&gt;
==Code Versions and Extensions==&lt;br /&gt;
&lt;br /&gt;
===Local and Global Versions===&lt;br /&gt;
&lt;br /&gt;
GENE can operate in different spatial modes:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Local (flux-tube)&#039;&#039;&#039; - simulates a small radial region with periodic boundary conditions; computationally efficient for core turbulence&lt;br /&gt;
* &#039;&#039;&#039;Radially global&#039;&#039;&#039; - includes variations across the plasma radius; necessary for edge effects and profile evolution&lt;br /&gt;
&lt;br /&gt;
===GENE-3D===&lt;br /&gt;
&lt;br /&gt;
GENE-3D is an extension that handles the complex three-dimensional geometry of stellarators. Development of GENE-3D took approximately five years and was presented by Maurice Maurer and colleagues.[3] Unlike the original tokamak-oriented version, GENE-3D can simulate the full ion and electron dynamics in the complex magnetic field geometry of stellarators like Wendelstein 7-X.&lt;br /&gt;
&lt;br /&gt;
===GENE-X===&lt;br /&gt;
&lt;br /&gt;
GENE-X is a full-f gyrokinetic continuum code based on the flux-coordinate independent (FCI) approach.[4] This version was developed specifically to handle:&lt;br /&gt;
&lt;br /&gt;
* Edge and scrape-off layer turbulence&lt;br /&gt;
* Regions with magnetic X-points (where traditional field-aligned coordinates have singularities)&lt;br /&gt;
* Geometries without well-defined flux surfaces&lt;br /&gt;
* Transition regions between core and edge plasma&lt;br /&gt;
&lt;br /&gt;
GENE-X uses unstructured, locally Cartesian grids that provide flexibility while maintaining computational efficiency. The code is capable of simulating regions from the magnetic axis, across the separatrix, and into the scrape-off layer.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Development and Community==&lt;br /&gt;
&lt;br /&gt;
===History===&lt;br /&gt;
&lt;br /&gt;
Frank Jenko wrote the first version of GENE in 1999 during his early postdoctoral work[1]. Since then, the code has been continuously developed and improved by an international team of researchers. Major development centers include:&lt;br /&gt;
&lt;br /&gt;
* Max Planck Institute for Plasma Physics (IPP), Garching, Germany&lt;br /&gt;
* Max Planck Computing and Data Facility (MPCDF), Germany&lt;br /&gt;
* Technical University of Munich, Germany&lt;br /&gt;
* University of Texas at Austin, USA&lt;br /&gt;
* École Polytechnique Fédérale de Lausanne (EPFL), Switzerland&lt;br /&gt;
* Many other international institutions&lt;br /&gt;
&lt;br /&gt;
===International Collaboration===&lt;br /&gt;
&lt;br /&gt;
The GENE Development Team is an international collaboration that includes members from universities and research laboratories across the world. The project welcomes contributions from the global fusion community and maintains an open-source development model.&lt;br /&gt;
&lt;br /&gt;
Institutions using GENE include research centers in Germany, USA, Switzerland, France, UK, Netherlands, Italy, Japan, India, China, South Korea, and many others.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===High-Performance Computing===&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
GENE has been at the forefront of high-performance computing in plasma physics since the 1960s. The code is designed to run efficiently on the world&#039;s largest supercomputers. In 2022, a major project was launched with €2.14 million in EU funding to develop an exascale version of GENE, pioneering the transition to exascale supercomputers.[5]&lt;br /&gt;
&lt;br /&gt;
The goal is to create &amp;quot;digital twins&amp;quot; of fusion experiments like ITER, allowing researchers to predict plasma behavior rather than just interpret experimental results.&lt;br /&gt;
&lt;br /&gt;
==Validation and Impact==&lt;br /&gt;
&lt;br /&gt;
GENE has been extensively validated against experimental measurements from major fusion devices. A landmark 2025 study demonstrated successful multi-channel validation of GENE against ASDEX Upgrade tokamak data, comparing simultaneous measurements of multiple plasma properties including turbulence amplitudes, wavenumber spectra, and cross phases.[2]&lt;br /&gt;
&lt;br /&gt;
The code has been used to:&lt;br /&gt;
* Explain turbulence suppression by fast ions in tokamak plasmas&lt;br /&gt;
* Predict similar effects in stellarators&lt;br /&gt;
* Understand energy confinement scaling&lt;br /&gt;
* Design optimal plasma scenarios for ITER&lt;br /&gt;
* Investigate the effects of different wall materials (like tungsten) on plasma performance&lt;br /&gt;
&lt;br /&gt;
==See also==&lt;br /&gt;
&lt;br /&gt;
* [[Gyrokinetic simulations]]&lt;br /&gt;
* [[Plasma Physics at the LNF]]&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Tokamak]]&lt;br /&gt;
* [[Stellarator]]&lt;br /&gt;
* [[ITER]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
* [[MHD equilibrium]]&lt;br /&gt;
&lt;br /&gt;
==References==&lt;br /&gt;
&lt;br /&gt;
# Jenko, F. (1999). &amp;quot;Development of GENE code&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/5295353/06_22&lt;br /&gt;
# &amp;quot;Milestone in predicting core plasma turbulence: successful multi-channel validation of the gyrokinetic code GENE&amp;quot; (2025). Nature Communications. https://www.nature.com/articles/s41467-025-56997-2&lt;br /&gt;
# Maurer, M. et al. &amp;quot;Promising computer simulations for stellarator plasmas&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/4928395/05_20&lt;br /&gt;
# &amp;quot;GENE-X: A full-f gyrokinetic turbulence code based on the flux-coordinate independent approach&amp;quot; (2021). Computer Physics Communications. https://www.sciencedirect.com/science/article/abs/pii/S0010465521000989&lt;br /&gt;
# &amp;quot;Nuclear fusion simulation to pioneer transition to exascale supercomputers&amp;quot; (2023). EUROfusion. Retrieved from https://euro-fusion.org/member-news/nuclear-fusion-simulation-to-pioneer-transition-to-exascale-supercomputers/&lt;br /&gt;
&lt;br /&gt;
==External links==&lt;br /&gt;
&lt;br /&gt;
* [https://genecode.org Official GENE website]&lt;br /&gt;
* [https://www.ipp.mpg.de Max Planck Institute for Plasma Physics]&lt;br /&gt;
* [https://genecode.org/license.html GENE license &amp;amp; how to obtain the source]&lt;br /&gt;
* [https://www.iter.org ITER Organization]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Category:Software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8552</id>
		<title>GENE</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8552"/>
		<updated>2026-02-09T22:04:09Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* External links */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&#039;&#039;&#039;GENE&#039;&#039;&#039; (&#039;&#039;&#039;Gyrokinetic Electromagnetic Numerical Experiment&#039;&#039;&#039;) is an open-source computer simulation code used to study plasma turbulence in magnetic confinement fusion devices. GENE solves the gyrokinetic equations to simulate electromagnetic turbulence in plasmas, which is critical for understanding energy confinement in fusion reactors like tokamaks and stellarators.&lt;br /&gt;
&lt;br /&gt;
==Overview==&lt;br /&gt;
&lt;br /&gt;
[https://genecode.org/ GENE] is a gyrokinetic turbulence code that simulates plasma behavior at very small scales comparable to the ion and electron gyroradius. The code was originally developed at the [https://www.ipp.mpg.de/ Max Planck Institute for Plasma Physics] in Garching, Germany, with the first version written by [https://www.ipp.mpg.de/4159541/jenko Frank Jenko] in 1999 [1].&lt;br /&gt;
&lt;br /&gt;
GENE is widely used in the international fusion research community and is considered one of the leading codes for plasma turbulence simulations. The code has been continuously developed by an international team of researchers and is designed to run on high-performance supercomputers.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Purpose and Applications===&lt;br /&gt;
&lt;br /&gt;
The main purpose of GENE is to understand and predict turbulent transport in fusion plasmas. Plasma turbulence is one of the key factors limiting energy confinement in magnetic fusion devices, which directly affects the performance and efficiency of potential fusion power plants. By simulating this turbulence, GENE helps researchers:&lt;br /&gt;
&lt;br /&gt;
* Predict energy confinement times in fusion experiments&lt;br /&gt;
* Understand heat and particle transport mechanisms&lt;br /&gt;
* Optimize plasma conditions for better performance&lt;br /&gt;
* Design future fusion devices including ITER&lt;br /&gt;
* Validate theoretical models against experimental data&lt;br /&gt;
&lt;br /&gt;
The code has been successfully validated against experimental measurements from major fusion devices including ASDEX Upgrade and has shown excellent agreement with multiple simultaneous plasma observables.&lt;br /&gt;
&lt;br /&gt;
==Physical Model==&lt;br /&gt;
&lt;br /&gt;
GENE is based on gyrokinetic theory, which describes plasma behavior on spatial scales comparable to particle gyroradii and on time scales much slower than the cyclotron frequency. This approach reduces the complexity of the full kinetic description while retaining the essential physics of plasma turbulence.&lt;br /&gt;
&lt;br /&gt;
===Gyrokinetic Equations===&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic model assumes that:&lt;br /&gt;
* The plasma is strongly magnetized&lt;br /&gt;
* Perpendicular spatial scales are comparable to the ion gyroradius&lt;br /&gt;
* Frequencies are much lower than the ion cyclotron frequency&lt;br /&gt;
* Perturbations are small compared to background quantities&lt;br /&gt;
&lt;br /&gt;
The fundamental equations solved by GENE include:&lt;br /&gt;
&lt;br /&gt;
====Gyrokinetic Vlasov Equation====&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic equation describes the evolution of the perturbed distribution function. In simplified form, it can be written as:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\frac{\partial h_s}{\partial t} + \mathbf{v}_{\text{gc}} \cdot \nabla h_s + \dot{v}_\parallel \frac{\partial h_s}{\partial v_\parallel} = C(h_s)&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
where:&lt;br /&gt;
* &amp;lt;math&amp;gt;h_s&amp;lt;/math&amp;gt; is the perturbed distribution function for species &#039;&#039;s&#039;&#039;&lt;br /&gt;
* &amp;lt;math&amp;gt;\mathbf{v}_{\text{gc}}&amp;lt;/math&amp;gt; is the guiding center velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;v_\parallel&amp;lt;/math&amp;gt; is the parallel velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;C(h_s)&amp;lt;/math&amp;gt; represents collisional effects&lt;br /&gt;
&lt;br /&gt;
====Maxwell&#039;s Equations====&lt;br /&gt;
&lt;br /&gt;
GENE couples the gyrokinetic equation to Maxwell&#039;s equations to determine the electromagnetic fields. In the electrostatic approximation, this reduces to the quasineutrality condition:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\sum_s Z_s e B \int dv_\parallel \, d\mu \, d\varphi \, h_s(\mathbf{R}) = \sum_s \frac{Z_s^2 e^2 n_s \phi}{T_s}&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
For electromagnetic simulations, GENE also solves Ampère&#039;s law for the parallel magnetic field perturbations.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Turbulence Mechanisms===&lt;br /&gt;
&lt;br /&gt;
GENE can simulate various types of plasma turbulence, including:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Ion Temperature Gradient (ITG) modes&#039;&#039;&#039; - driven by temperature gradients in the plasma&lt;br /&gt;
* &#039;&#039;&#039;Trapped Electron Modes (TEM)&#039;&#039;&#039; - caused by particles trapped in magnetic field variations&lt;br /&gt;
* &#039;&#039;&#039;Electron Temperature Gradient (ETG) modes&#039;&#039;&#039; - electron-scale turbulence&lt;br /&gt;
* &#039;&#039;&#039;Kinetic Ballooning Modes (KBM)&#039;&#039;&#039; - pressure-driven instabilities&lt;br /&gt;
* &#039;&#039;&#039;Microtearing modes&#039;&#039;&#039; - electromagnetic instabilities that can tear magnetic field lines&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Numerical Methods==&lt;br /&gt;
&lt;br /&gt;
GENE is a Eulerian code, meaning it solves the gyrokinetic equations on a fixed grid in phase space rather than following individual particles. This approach has several advantages for turbulence simulations.&lt;br /&gt;
&lt;br /&gt;
===Discretization===&lt;br /&gt;
&lt;br /&gt;
The code uses a combination of numerical methods:&lt;br /&gt;
* &#039;&#039;&#039;Spectral methods&#039;&#039;&#039; in the perpendicular directions (for periodic boundary conditions)&lt;br /&gt;
* &#039;&#039;&#039;Finite differences&#039;&#039;&#039; in the radial direction (for global simulations)&lt;br /&gt;
* &#039;&#039;&#039;Upwind schemes&#039;&#039;&#039; along magnetic field lines&lt;br /&gt;
* &#039;&#039;&#039;Runge-Kutta methods&#039;&#039;&#039; for time integration&lt;br /&gt;
&lt;br /&gt;
===Coordinate Systems===&lt;br /&gt;
&lt;br /&gt;
GENE employs field-aligned coordinates that follow magnetic field lines, which is natural for strongly magnetized plasmas. Different versions of the code use different coordinate approaches:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Standard GENE&#039;&#039;&#039; - uses flux-tube or radially global geometry in tokamaks&lt;br /&gt;
* &#039;&#039;&#039;GENE-3D&#039;&#039;&#039; - full three-dimensional geometry for stellarators&lt;br /&gt;
* &#039;&#039;&#039;GENE-X&#039;&#039;&#039; - flux-coordinate independent (FCI) approach for edge and scrape-off layer regions&lt;br /&gt;
&lt;br /&gt;
==Code Versions and Extensions==&lt;br /&gt;
&lt;br /&gt;
===Local and Global Versions===&lt;br /&gt;
&lt;br /&gt;
GENE can operate in different spatial modes:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Local (flux-tube)&#039;&#039;&#039; - simulates a small radial region with periodic boundary conditions; computationally efficient for core turbulence&lt;br /&gt;
* &#039;&#039;&#039;Radially global&#039;&#039;&#039; - includes variations across the plasma radius; necessary for edge effects and profile evolution&lt;br /&gt;
&lt;br /&gt;
===GENE-3D===&lt;br /&gt;
&lt;br /&gt;
GENE-3D is an extension that handles the complex three-dimensional geometry of stellarators. Development of GENE-3D took approximately five years and was presented by Maurice Maurer and colleagues.[3] Unlike the original tokamak-oriented version, GENE-3D can simulate the full ion and electron dynamics in the complex magnetic field geometry of stellarators like Wendelstein 7-X.&lt;br /&gt;
&lt;br /&gt;
===GENE-X===&lt;br /&gt;
&lt;br /&gt;
GENE-X is a full-f gyrokinetic continuum code based on the flux-coordinate independent (FCI) approach.[4] This version was developed specifically to handle:&lt;br /&gt;
&lt;br /&gt;
* Edge and scrape-off layer turbulence&lt;br /&gt;
* Regions with magnetic X-points (where traditional field-aligned coordinates have singularities)&lt;br /&gt;
* Geometries without well-defined flux surfaces&lt;br /&gt;
* Transition regions between core and edge plasma&lt;br /&gt;
&lt;br /&gt;
GENE-X uses unstructured, locally Cartesian grids that provide flexibility while maintaining computational efficiency. The code is capable of simulating regions from the magnetic axis, across the separatrix, and into the scrape-off layer.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Development and Community==&lt;br /&gt;
&lt;br /&gt;
===History===&lt;br /&gt;
&lt;br /&gt;
Frank Jenko wrote the first version of GENE in 1999 during his early postdoctoral work[1]. Since then, the code has been continuously developed and improved by an international team of researchers. Major development centers include:&lt;br /&gt;
&lt;br /&gt;
* Max Planck Institute for Plasma Physics (IPP), Garching, Germany&lt;br /&gt;
* Max Planck Computing and Data Facility (MPCDF), Germany&lt;br /&gt;
* Technical University of Munich, Germany&lt;br /&gt;
* University of Texas at Austin, USA&lt;br /&gt;
* École Polytechnique Fédérale de Lausanne (EPFL), Switzerland&lt;br /&gt;
* Many other international institutions&lt;br /&gt;
&lt;br /&gt;
===International Collaboration===&lt;br /&gt;
&lt;br /&gt;
The GENE Development Team is an international collaboration that includes members from universities and research laboratories across the world. The project welcomes contributions from the global fusion community and maintains an open-source development model.&lt;br /&gt;
&lt;br /&gt;
Institutions using GENE include research centers in Germany, USA, Switzerland, France, UK, Netherlands, Italy, Japan, India, China, South Korea, and many others.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===High-Performance Computing===&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
GENE has been at the forefront of high-performance computing in plasma physics since the 1960s. The code is designed to run efficiently on the world&#039;s largest supercomputers. In 2022, a major project was launched with €2.14 million in EU funding to develop an exascale version of GENE, pioneering the transition to exascale supercomputers.[5]&lt;br /&gt;
&lt;br /&gt;
The goal is to create &amp;quot;digital twins&amp;quot; of fusion experiments like ITER, allowing researchers to predict plasma behavior rather than just interpret experimental results.&lt;br /&gt;
&lt;br /&gt;
==Validation and Impact==&lt;br /&gt;
&lt;br /&gt;
GENE has been extensively validated against experimental measurements from major fusion devices. A landmark 2025 study demonstrated successful multi-channel validation of GENE against ASDEX Upgrade tokamak data, comparing simultaneous measurements of multiple plasma properties including turbulence amplitudes, wavenumber spectra, and cross phases.[2]&lt;br /&gt;
&lt;br /&gt;
The code has been used to:&lt;br /&gt;
* Explain turbulence suppression by fast ions in tokamak plasmas&lt;br /&gt;
* Predict similar effects in stellarators&lt;br /&gt;
* Understand energy confinement scaling&lt;br /&gt;
* Design optimal plasma scenarios for ITER&lt;br /&gt;
* Investigate the effects of different wall materials (like tungsten) on plasma performance&lt;br /&gt;
&lt;br /&gt;
==See also==&lt;br /&gt;
&lt;br /&gt;
* [[Gyrokinetic simulations]]&lt;br /&gt;
* [[Plasma Physics at the LNF]]&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Tokamak]]&lt;br /&gt;
* [[Stellarator]]&lt;br /&gt;
* [[ITER]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
* [[MHD equilibrium]]&lt;br /&gt;
&lt;br /&gt;
==References==&lt;br /&gt;
&lt;br /&gt;
# Jenko, F. (1999). &amp;quot;Development of GENE code&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/5295353/06_22&lt;br /&gt;
# &amp;quot;Milestone in predicting core plasma turbulence: successful multi-channel validation of the gyrokinetic code GENE&amp;quot; (2025). Nature Communications. https://www.nature.com/articles/s41467-025-56997-2&lt;br /&gt;
# Maurer, M. et al. &amp;quot;Promising computer simulations for stellarator plasmas&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/4928395/05_20&lt;br /&gt;
# &amp;quot;GENE-X: A full-f gyrokinetic turbulence code based on the flux-coordinate independent approach&amp;quot; (2021). Computer Physics Communications. https://www.sciencedirect.com/science/article/abs/pii/S0010465521000989&lt;br /&gt;
# &amp;quot;Nuclear fusion simulation to pioneer transition to exascale supercomputers&amp;quot; (2023). EUROfusion. Retrieved from https://euro-fusion.org/member-news/nuclear-fusion-simulation-to-pioneer-transition-to-exascale-supercomputers/&lt;br /&gt;
&lt;br /&gt;
==External links==&lt;br /&gt;
&lt;br /&gt;
* [https://genecode.org Official GENE website]&lt;br /&gt;
* [https://www.ipp.mpg.de Max Planck Institute for Plasma Physics]&lt;br /&gt;
* [https://genecode.org/license.html GENE license &amp;amp; how to obtain the source]&lt;br /&gt;
* [https://www.iter.org ITER Organization]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Category:Plasma physics]]&lt;br /&gt;
[[Category:Nuclear fusion]]&lt;br /&gt;
[[Category:Computational physics]]&lt;br /&gt;
[[Category:Scientific simulation software]]&lt;br /&gt;
[[Category:Physics software]]&lt;br /&gt;
[[Category:Free science software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8551</id>
		<title>GENE</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8551"/>
		<updated>2026-02-09T22:00:13Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* See also */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&#039;&#039;&#039;GENE&#039;&#039;&#039; (&#039;&#039;&#039;Gyrokinetic Electromagnetic Numerical Experiment&#039;&#039;&#039;) is an open-source computer simulation code used to study plasma turbulence in magnetic confinement fusion devices. GENE solves the gyrokinetic equations to simulate electromagnetic turbulence in plasmas, which is critical for understanding energy confinement in fusion reactors like tokamaks and stellarators.&lt;br /&gt;
&lt;br /&gt;
==Overview==&lt;br /&gt;
&lt;br /&gt;
[https://genecode.org/ GENE] is a gyrokinetic turbulence code that simulates plasma behavior at very small scales comparable to the ion and electron gyroradius. The code was originally developed at the [https://www.ipp.mpg.de/ Max Planck Institute for Plasma Physics] in Garching, Germany, with the first version written by [https://www.ipp.mpg.de/4159541/jenko Frank Jenko] in 1999 [1].&lt;br /&gt;
&lt;br /&gt;
GENE is widely used in the international fusion research community and is considered one of the leading codes for plasma turbulence simulations. The code has been continuously developed by an international team of researchers and is designed to run on high-performance supercomputers.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Purpose and Applications===&lt;br /&gt;
&lt;br /&gt;
The main purpose of GENE is to understand and predict turbulent transport in fusion plasmas. Plasma turbulence is one of the key factors limiting energy confinement in magnetic fusion devices, which directly affects the performance and efficiency of potential fusion power plants. By simulating this turbulence, GENE helps researchers:&lt;br /&gt;
&lt;br /&gt;
* Predict energy confinement times in fusion experiments&lt;br /&gt;
* Understand heat and particle transport mechanisms&lt;br /&gt;
* Optimize plasma conditions for better performance&lt;br /&gt;
* Design future fusion devices including ITER&lt;br /&gt;
* Validate theoretical models against experimental data&lt;br /&gt;
&lt;br /&gt;
The code has been successfully validated against experimental measurements from major fusion devices including ASDEX Upgrade and has shown excellent agreement with multiple simultaneous plasma observables.&lt;br /&gt;
&lt;br /&gt;
==Physical Model==&lt;br /&gt;
&lt;br /&gt;
GENE is based on gyrokinetic theory, which describes plasma behavior on spatial scales comparable to particle gyroradii and on time scales much slower than the cyclotron frequency. This approach reduces the complexity of the full kinetic description while retaining the essential physics of plasma turbulence.&lt;br /&gt;
&lt;br /&gt;
===Gyrokinetic Equations===&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic model assumes that:&lt;br /&gt;
* The plasma is strongly magnetized&lt;br /&gt;
* Perpendicular spatial scales are comparable to the ion gyroradius&lt;br /&gt;
* Frequencies are much lower than the ion cyclotron frequency&lt;br /&gt;
* Perturbations are small compared to background quantities&lt;br /&gt;
&lt;br /&gt;
The fundamental equations solved by GENE include:&lt;br /&gt;
&lt;br /&gt;
====Gyrokinetic Vlasov Equation====&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic equation describes the evolution of the perturbed distribution function. In simplified form, it can be written as:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\frac{\partial h_s}{\partial t} + \mathbf{v}_{\text{gc}} \cdot \nabla h_s + \dot{v}_\parallel \frac{\partial h_s}{\partial v_\parallel} = C(h_s)&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
where:&lt;br /&gt;
* &amp;lt;math&amp;gt;h_s&amp;lt;/math&amp;gt; is the perturbed distribution function for species &#039;&#039;s&#039;&#039;&lt;br /&gt;
* &amp;lt;math&amp;gt;\mathbf{v}_{\text{gc}}&amp;lt;/math&amp;gt; is the guiding center velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;v_\parallel&amp;lt;/math&amp;gt; is the parallel velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;C(h_s)&amp;lt;/math&amp;gt; represents collisional effects&lt;br /&gt;
&lt;br /&gt;
====Maxwell&#039;s Equations====&lt;br /&gt;
&lt;br /&gt;
GENE couples the gyrokinetic equation to Maxwell&#039;s equations to determine the electromagnetic fields. In the electrostatic approximation, this reduces to the quasineutrality condition:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\sum_s Z_s e B \int dv_\parallel \, d\mu \, d\varphi \, h_s(\mathbf{R}) = \sum_s \frac{Z_s^2 e^2 n_s \phi}{T_s}&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
For electromagnetic simulations, GENE also solves Ampère&#039;s law for the parallel magnetic field perturbations.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Turbulence Mechanisms===&lt;br /&gt;
&lt;br /&gt;
GENE can simulate various types of plasma turbulence, including:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Ion Temperature Gradient (ITG) modes&#039;&#039;&#039; - driven by temperature gradients in the plasma&lt;br /&gt;
* &#039;&#039;&#039;Trapped Electron Modes (TEM)&#039;&#039;&#039; - caused by particles trapped in magnetic field variations&lt;br /&gt;
* &#039;&#039;&#039;Electron Temperature Gradient (ETG) modes&#039;&#039;&#039; - electron-scale turbulence&lt;br /&gt;
* &#039;&#039;&#039;Kinetic Ballooning Modes (KBM)&#039;&#039;&#039; - pressure-driven instabilities&lt;br /&gt;
* &#039;&#039;&#039;Microtearing modes&#039;&#039;&#039; - electromagnetic instabilities that can tear magnetic field lines&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Numerical Methods==&lt;br /&gt;
&lt;br /&gt;
GENE is a Eulerian code, meaning it solves the gyrokinetic equations on a fixed grid in phase space rather than following individual particles. This approach has several advantages for turbulence simulations.&lt;br /&gt;
&lt;br /&gt;
===Discretization===&lt;br /&gt;
&lt;br /&gt;
The code uses a combination of numerical methods:&lt;br /&gt;
* &#039;&#039;&#039;Spectral methods&#039;&#039;&#039; in the perpendicular directions (for periodic boundary conditions)&lt;br /&gt;
* &#039;&#039;&#039;Finite differences&#039;&#039;&#039; in the radial direction (for global simulations)&lt;br /&gt;
* &#039;&#039;&#039;Upwind schemes&#039;&#039;&#039; along magnetic field lines&lt;br /&gt;
* &#039;&#039;&#039;Runge-Kutta methods&#039;&#039;&#039; for time integration&lt;br /&gt;
&lt;br /&gt;
===Coordinate Systems===&lt;br /&gt;
&lt;br /&gt;
GENE employs field-aligned coordinates that follow magnetic field lines, which is natural for strongly magnetized plasmas. Different versions of the code use different coordinate approaches:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Standard GENE&#039;&#039;&#039; - uses flux-tube or radially global geometry in tokamaks&lt;br /&gt;
* &#039;&#039;&#039;GENE-3D&#039;&#039;&#039; - full three-dimensional geometry for stellarators&lt;br /&gt;
* &#039;&#039;&#039;GENE-X&#039;&#039;&#039; - flux-coordinate independent (FCI) approach for edge and scrape-off layer regions&lt;br /&gt;
&lt;br /&gt;
==Code Versions and Extensions==&lt;br /&gt;
&lt;br /&gt;
===Local and Global Versions===&lt;br /&gt;
&lt;br /&gt;
GENE can operate in different spatial modes:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Local (flux-tube)&#039;&#039;&#039; - simulates a small radial region with periodic boundary conditions; computationally efficient for core turbulence&lt;br /&gt;
* &#039;&#039;&#039;Radially global&#039;&#039;&#039; - includes variations across the plasma radius; necessary for edge effects and profile evolution&lt;br /&gt;
&lt;br /&gt;
===GENE-3D===&lt;br /&gt;
&lt;br /&gt;
GENE-3D is an extension that handles the complex three-dimensional geometry of stellarators. Development of GENE-3D took approximately five years and was presented by Maurice Maurer and colleagues.[3] Unlike the original tokamak-oriented version, GENE-3D can simulate the full ion and electron dynamics in the complex magnetic field geometry of stellarators like Wendelstein 7-X.&lt;br /&gt;
&lt;br /&gt;
===GENE-X===&lt;br /&gt;
&lt;br /&gt;
GENE-X is a full-f gyrokinetic continuum code based on the flux-coordinate independent (FCI) approach.[4] This version was developed specifically to handle:&lt;br /&gt;
&lt;br /&gt;
* Edge and scrape-off layer turbulence&lt;br /&gt;
* Regions with magnetic X-points (where traditional field-aligned coordinates have singularities)&lt;br /&gt;
* Geometries without well-defined flux surfaces&lt;br /&gt;
* Transition regions between core and edge plasma&lt;br /&gt;
&lt;br /&gt;
GENE-X uses unstructured, locally Cartesian grids that provide flexibility while maintaining computational efficiency. The code is capable of simulating regions from the magnetic axis, across the separatrix, and into the scrape-off layer.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Development and Community==&lt;br /&gt;
&lt;br /&gt;
===History===&lt;br /&gt;
&lt;br /&gt;
Frank Jenko wrote the first version of GENE in 1999 during his early postdoctoral work[1]. Since then, the code has been continuously developed and improved by an international team of researchers. Major development centers include:&lt;br /&gt;
&lt;br /&gt;
* Max Planck Institute for Plasma Physics (IPP), Garching, Germany&lt;br /&gt;
* Max Planck Computing and Data Facility (MPCDF), Germany&lt;br /&gt;
* Technical University of Munich, Germany&lt;br /&gt;
* University of Texas at Austin, USA&lt;br /&gt;
* École Polytechnique Fédérale de Lausanne (EPFL), Switzerland&lt;br /&gt;
* Many other international institutions&lt;br /&gt;
&lt;br /&gt;
===International Collaboration===&lt;br /&gt;
&lt;br /&gt;
The GENE Development Team is an international collaboration that includes members from universities and research laboratories across the world. The project welcomes contributions from the global fusion community and maintains an open-source development model.&lt;br /&gt;
&lt;br /&gt;
Institutions using GENE include research centers in Germany, USA, Switzerland, France, UK, Netherlands, Italy, Japan, India, China, South Korea, and many others.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===High-Performance Computing===&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
GENE has been at the forefront of high-performance computing in plasma physics since the 1960s. The code is designed to run efficiently on the world&#039;s largest supercomputers. In 2022, a major project was launched with €2.14 million in EU funding to develop an exascale version of GENE, pioneering the transition to exascale supercomputers.[5]&lt;br /&gt;
&lt;br /&gt;
The goal is to create &amp;quot;digital twins&amp;quot; of fusion experiments like ITER, allowing researchers to predict plasma behavior rather than just interpret experimental results.&lt;br /&gt;
&lt;br /&gt;
==Validation and Impact==&lt;br /&gt;
&lt;br /&gt;
GENE has been extensively validated against experimental measurements from major fusion devices. A landmark 2025 study demonstrated successful multi-channel validation of GENE against ASDEX Upgrade tokamak data, comparing simultaneous measurements of multiple plasma properties including turbulence amplitudes, wavenumber spectra, and cross phases.[2]&lt;br /&gt;
&lt;br /&gt;
The code has been used to:&lt;br /&gt;
* Explain turbulence suppression by fast ions in tokamak plasmas&lt;br /&gt;
* Predict similar effects in stellarators&lt;br /&gt;
* Understand energy confinement scaling&lt;br /&gt;
* Design optimal plasma scenarios for ITER&lt;br /&gt;
* Investigate the effects of different wall materials (like tungsten) on plasma performance&lt;br /&gt;
&lt;br /&gt;
==See also==&lt;br /&gt;
&lt;br /&gt;
* [[Gyrokinetic simulations]]&lt;br /&gt;
* [[Plasma Physics at the LNF]]&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Tokamak]]&lt;br /&gt;
* [[Stellarator]]&lt;br /&gt;
* [[ITER]]&lt;br /&gt;
* [[Plasma simulation]]&lt;br /&gt;
* [[MHD equilibrium]]&lt;br /&gt;
&lt;br /&gt;
==References==&lt;br /&gt;
&lt;br /&gt;
# Jenko, F. (1999). &amp;quot;Development of GENE code&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/5295353/06_22&lt;br /&gt;
# &amp;quot;Milestone in predicting core plasma turbulence: successful multi-channel validation of the gyrokinetic code GENE&amp;quot; (2025). Nature Communications. https://www.nature.com/articles/s41467-025-56997-2&lt;br /&gt;
# Maurer, M. et al. &amp;quot;Promising computer simulations for stellarator plasmas&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/4928395/05_20&lt;br /&gt;
# &amp;quot;GENE-X: A full-f gyrokinetic turbulence code based on the flux-coordinate independent approach&amp;quot; (2021). Computer Physics Communications. https://www.sciencedirect.com/science/article/abs/pii/S0010465521000989&lt;br /&gt;
# &amp;quot;Nuclear fusion simulation to pioneer transition to exascale supercomputers&amp;quot; (2023). EUROfusion. Retrieved from https://euro-fusion.org/member-news/nuclear-fusion-simulation-to-pioneer-transition-to-exascale-supercomputers/&lt;br /&gt;
&lt;br /&gt;
==External links==&lt;br /&gt;
&lt;br /&gt;
* [https://genecode.org Official GENE website]&lt;br /&gt;
* [https://www.ipp.mpg.de Max Planck Institute for Plasma Physics]&lt;br /&gt;
* [https://github.com/genestrucutretest/GENE GENE on GitHub] (if available)&lt;br /&gt;
* [https://www.iter.org ITER Organization]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Category:Plasma physics]]&lt;br /&gt;
[[Category:Nuclear fusion]]&lt;br /&gt;
[[Category:Computational physics]]&lt;br /&gt;
[[Category:Scientific simulation software]]&lt;br /&gt;
[[Category:Physics software]]&lt;br /&gt;
[[Category:Free science software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8550</id>
		<title>GENE</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8550"/>
		<updated>2026-02-09T21:57:19Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* See also */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&#039;&#039;&#039;GENE&#039;&#039;&#039; (&#039;&#039;&#039;Gyrokinetic Electromagnetic Numerical Experiment&#039;&#039;&#039;) is an open-source computer simulation code used to study plasma turbulence in magnetic confinement fusion devices. GENE solves the gyrokinetic equations to simulate electromagnetic turbulence in plasmas, which is critical for understanding energy confinement in fusion reactors like tokamaks and stellarators.&lt;br /&gt;
&lt;br /&gt;
==Overview==&lt;br /&gt;
&lt;br /&gt;
[https://genecode.org/ GENE] is a gyrokinetic turbulence code that simulates plasma behavior at very small scales comparable to the ion and electron gyroradius. The code was originally developed at the [https://www.ipp.mpg.de/ Max Planck Institute for Plasma Physics] in Garching, Germany, with the first version written by [https://www.ipp.mpg.de/4159541/jenko Frank Jenko] in 1999 [1].&lt;br /&gt;
&lt;br /&gt;
GENE is widely used in the international fusion research community and is considered one of the leading codes for plasma turbulence simulations. The code has been continuously developed by an international team of researchers and is designed to run on high-performance supercomputers.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Purpose and Applications===&lt;br /&gt;
&lt;br /&gt;
The main purpose of GENE is to understand and predict turbulent transport in fusion plasmas. Plasma turbulence is one of the key factors limiting energy confinement in magnetic fusion devices, which directly affects the performance and efficiency of potential fusion power plants. By simulating this turbulence, GENE helps researchers:&lt;br /&gt;
&lt;br /&gt;
* Predict energy confinement times in fusion experiments&lt;br /&gt;
* Understand heat and particle transport mechanisms&lt;br /&gt;
* Optimize plasma conditions for better performance&lt;br /&gt;
* Design future fusion devices including ITER&lt;br /&gt;
* Validate theoretical models against experimental data&lt;br /&gt;
&lt;br /&gt;
The code has been successfully validated against experimental measurements from major fusion devices including ASDEX Upgrade and has shown excellent agreement with multiple simultaneous plasma observables.&lt;br /&gt;
&lt;br /&gt;
==Physical Model==&lt;br /&gt;
&lt;br /&gt;
GENE is based on gyrokinetic theory, which describes plasma behavior on spatial scales comparable to particle gyroradii and on time scales much slower than the cyclotron frequency. This approach reduces the complexity of the full kinetic description while retaining the essential physics of plasma turbulence.&lt;br /&gt;
&lt;br /&gt;
===Gyrokinetic Equations===&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic model assumes that:&lt;br /&gt;
* The plasma is strongly magnetized&lt;br /&gt;
* Perpendicular spatial scales are comparable to the ion gyroradius&lt;br /&gt;
* Frequencies are much lower than the ion cyclotron frequency&lt;br /&gt;
* Perturbations are small compared to background quantities&lt;br /&gt;
&lt;br /&gt;
The fundamental equations solved by GENE include:&lt;br /&gt;
&lt;br /&gt;
====Gyrokinetic Vlasov Equation====&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic equation describes the evolution of the perturbed distribution function. In simplified form, it can be written as:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\frac{\partial h_s}{\partial t} + \mathbf{v}_{\text{gc}} \cdot \nabla h_s + \dot{v}_\parallel \frac{\partial h_s}{\partial v_\parallel} = C(h_s)&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
where:&lt;br /&gt;
* &amp;lt;math&amp;gt;h_s&amp;lt;/math&amp;gt; is the perturbed distribution function for species &#039;&#039;s&#039;&#039;&lt;br /&gt;
* &amp;lt;math&amp;gt;\mathbf{v}_{\text{gc}}&amp;lt;/math&amp;gt; is the guiding center velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;v_\parallel&amp;lt;/math&amp;gt; is the parallel velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;C(h_s)&amp;lt;/math&amp;gt; represents collisional effects&lt;br /&gt;
&lt;br /&gt;
====Maxwell&#039;s Equations====&lt;br /&gt;
&lt;br /&gt;
GENE couples the gyrokinetic equation to Maxwell&#039;s equations to determine the electromagnetic fields. In the electrostatic approximation, this reduces to the quasineutrality condition:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\sum_s Z_s e B \int dv_\parallel \, d\mu \, d\varphi \, h_s(\mathbf{R}) = \sum_s \frac{Z_s^2 e^2 n_s \phi}{T_s}&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
For electromagnetic simulations, GENE also solves Ampère&#039;s law for the parallel magnetic field perturbations.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Turbulence Mechanisms===&lt;br /&gt;
&lt;br /&gt;
GENE can simulate various types of plasma turbulence, including:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Ion Temperature Gradient (ITG) modes&#039;&#039;&#039; - driven by temperature gradients in the plasma&lt;br /&gt;
* &#039;&#039;&#039;Trapped Electron Modes (TEM)&#039;&#039;&#039; - caused by particles trapped in magnetic field variations&lt;br /&gt;
* &#039;&#039;&#039;Electron Temperature Gradient (ETG) modes&#039;&#039;&#039; - electron-scale turbulence&lt;br /&gt;
* &#039;&#039;&#039;Kinetic Ballooning Modes (KBM)&#039;&#039;&#039; - pressure-driven instabilities&lt;br /&gt;
* &#039;&#039;&#039;Microtearing modes&#039;&#039;&#039; - electromagnetic instabilities that can tear magnetic field lines&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Numerical Methods==&lt;br /&gt;
&lt;br /&gt;
GENE is a Eulerian code, meaning it solves the gyrokinetic equations on a fixed grid in phase space rather than following individual particles. This approach has several advantages for turbulence simulations.&lt;br /&gt;
&lt;br /&gt;
===Discretization===&lt;br /&gt;
&lt;br /&gt;
The code uses a combination of numerical methods:&lt;br /&gt;
* &#039;&#039;&#039;Spectral methods&#039;&#039;&#039; in the perpendicular directions (for periodic boundary conditions)&lt;br /&gt;
* &#039;&#039;&#039;Finite differences&#039;&#039;&#039; in the radial direction (for global simulations)&lt;br /&gt;
* &#039;&#039;&#039;Upwind schemes&#039;&#039;&#039; along magnetic field lines&lt;br /&gt;
* &#039;&#039;&#039;Runge-Kutta methods&#039;&#039;&#039; for time integration&lt;br /&gt;
&lt;br /&gt;
===Coordinate Systems===&lt;br /&gt;
&lt;br /&gt;
GENE employs field-aligned coordinates that follow magnetic field lines, which is natural for strongly magnetized plasmas. Different versions of the code use different coordinate approaches:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Standard GENE&#039;&#039;&#039; - uses flux-tube or radially global geometry in tokamaks&lt;br /&gt;
* &#039;&#039;&#039;GENE-3D&#039;&#039;&#039; - full three-dimensional geometry for stellarators&lt;br /&gt;
* &#039;&#039;&#039;GENE-X&#039;&#039;&#039; - flux-coordinate independent (FCI) approach for edge and scrape-off layer regions&lt;br /&gt;
&lt;br /&gt;
==Code Versions and Extensions==&lt;br /&gt;
&lt;br /&gt;
===Local and Global Versions===&lt;br /&gt;
&lt;br /&gt;
GENE can operate in different spatial modes:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Local (flux-tube)&#039;&#039;&#039; - simulates a small radial region with periodic boundary conditions; computationally efficient for core turbulence&lt;br /&gt;
* &#039;&#039;&#039;Radially global&#039;&#039;&#039; - includes variations across the plasma radius; necessary for edge effects and profile evolution&lt;br /&gt;
&lt;br /&gt;
===GENE-3D===&lt;br /&gt;
&lt;br /&gt;
GENE-3D is an extension that handles the complex three-dimensional geometry of stellarators. Development of GENE-3D took approximately five years and was presented by Maurice Maurer and colleagues.[3] Unlike the original tokamak-oriented version, GENE-3D can simulate the full ion and electron dynamics in the complex magnetic field geometry of stellarators like Wendelstein 7-X.&lt;br /&gt;
&lt;br /&gt;
===GENE-X===&lt;br /&gt;
&lt;br /&gt;
GENE-X is a full-f gyrokinetic continuum code based on the flux-coordinate independent (FCI) approach.[4] This version was developed specifically to handle:&lt;br /&gt;
&lt;br /&gt;
* Edge and scrape-off layer turbulence&lt;br /&gt;
* Regions with magnetic X-points (where traditional field-aligned coordinates have singularities)&lt;br /&gt;
* Geometries without well-defined flux surfaces&lt;br /&gt;
* Transition regions between core and edge plasma&lt;br /&gt;
&lt;br /&gt;
GENE-X uses unstructured, locally Cartesian grids that provide flexibility while maintaining computational efficiency. The code is capable of simulating regions from the magnetic axis, across the separatrix, and into the scrape-off layer.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Development and Community==&lt;br /&gt;
&lt;br /&gt;
===History===&lt;br /&gt;
&lt;br /&gt;
Frank Jenko wrote the first version of GENE in 1999 during his early postdoctoral work[1]. Since then, the code has been continuously developed and improved by an international team of researchers. Major development centers include:&lt;br /&gt;
&lt;br /&gt;
* Max Planck Institute for Plasma Physics (IPP), Garching, Germany&lt;br /&gt;
* Max Planck Computing and Data Facility (MPCDF), Germany&lt;br /&gt;
* Technical University of Munich, Germany&lt;br /&gt;
* University of Texas at Austin, USA&lt;br /&gt;
* École Polytechnique Fédérale de Lausanne (EPFL), Switzerland&lt;br /&gt;
* Many other international institutions&lt;br /&gt;
&lt;br /&gt;
===International Collaboration===&lt;br /&gt;
&lt;br /&gt;
The GENE Development Team is an international collaboration that includes members from universities and research laboratories across the world. The project welcomes contributions from the global fusion community and maintains an open-source development model.&lt;br /&gt;
&lt;br /&gt;
Institutions using GENE include research centers in Germany, USA, Switzerland, France, UK, Netherlands, Italy, Japan, India, China, South Korea, and many others.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===High-Performance Computing===&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
GENE has been at the forefront of high-performance computing in plasma physics since the 1960s. The code is designed to run efficiently on the world&#039;s largest supercomputers. In 2022, a major project was launched with €2.14 million in EU funding to develop an exascale version of GENE, pioneering the transition to exascale supercomputers.[5]&lt;br /&gt;
&lt;br /&gt;
The goal is to create &amp;quot;digital twins&amp;quot; of fusion experiments like ITER, allowing researchers to predict plasma behavior rather than just interpret experimental results.&lt;br /&gt;
&lt;br /&gt;
==Validation and Impact==&lt;br /&gt;
&lt;br /&gt;
GENE has been extensively validated against experimental measurements from major fusion devices. A landmark 2025 study demonstrated successful multi-channel validation of GENE against ASDEX Upgrade tokamak data, comparing simultaneous measurements of multiple plasma properties including turbulence amplitudes, wavenumber spectra, and cross phases.[2]&lt;br /&gt;
&lt;br /&gt;
The code has been used to:&lt;br /&gt;
* Explain turbulence suppression by fast ions in tokamak plasmas&lt;br /&gt;
* Predict similar effects in stellarators&lt;br /&gt;
* Understand energy confinement scaling&lt;br /&gt;
* Design optimal plasma scenarios for ITER&lt;br /&gt;
* Investigate the effects of different wall materials (like tungsten) on plasma performance&lt;br /&gt;
&lt;br /&gt;
==See also==&lt;br /&gt;
&lt;br /&gt;
* [[Gyrokinetic simulations]]&lt;br /&gt;
* [[Plasma (physics)]]&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Tokamak]]&lt;br /&gt;
* [[Stellarator]]&lt;br /&gt;
* [[ITER]]&lt;br /&gt;
* [[Max Planck Institute for Plasma Physics]]&lt;br /&gt;
* [[Computational plasma physics]]&lt;br /&gt;
* [[Magnetohydrodynamics]]&lt;br /&gt;
&lt;br /&gt;
==References==&lt;br /&gt;
&lt;br /&gt;
# Jenko, F. (1999). &amp;quot;Development of GENE code&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/5295353/06_22&lt;br /&gt;
# &amp;quot;Milestone in predicting core plasma turbulence: successful multi-channel validation of the gyrokinetic code GENE&amp;quot; (2025). Nature Communications. https://www.nature.com/articles/s41467-025-56997-2&lt;br /&gt;
# Maurer, M. et al. &amp;quot;Promising computer simulations for stellarator plasmas&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/4928395/05_20&lt;br /&gt;
# &amp;quot;GENE-X: A full-f gyrokinetic turbulence code based on the flux-coordinate independent approach&amp;quot; (2021). Computer Physics Communications. https://www.sciencedirect.com/science/article/abs/pii/S0010465521000989&lt;br /&gt;
# &amp;quot;Nuclear fusion simulation to pioneer transition to exascale supercomputers&amp;quot; (2023). EUROfusion. Retrieved from https://euro-fusion.org/member-news/nuclear-fusion-simulation-to-pioneer-transition-to-exascale-supercomputers/&lt;br /&gt;
&lt;br /&gt;
==External links==&lt;br /&gt;
&lt;br /&gt;
* [https://genecode.org Official GENE website]&lt;br /&gt;
* [https://www.ipp.mpg.de Max Planck Institute for Plasma Physics]&lt;br /&gt;
* [https://github.com/genestrucutretest/GENE GENE on GitHub] (if available)&lt;br /&gt;
* [https://www.iter.org ITER Organization]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Category:Plasma physics]]&lt;br /&gt;
[[Category:Nuclear fusion]]&lt;br /&gt;
[[Category:Computational physics]]&lt;br /&gt;
[[Category:Scientific simulation software]]&lt;br /&gt;
[[Category:Physics software]]&lt;br /&gt;
[[Category:Free science software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8549</id>
		<title>GENE</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8549"/>
		<updated>2026-02-09T21:56:44Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&#039;&#039;&#039;GENE&#039;&#039;&#039; (&#039;&#039;&#039;Gyrokinetic Electromagnetic Numerical Experiment&#039;&#039;&#039;) is an open-source computer simulation code used to study plasma turbulence in magnetic confinement fusion devices. GENE solves the gyrokinetic equations to simulate electromagnetic turbulence in plasmas, which is critical for understanding energy confinement in fusion reactors like tokamaks and stellarators.&lt;br /&gt;
&lt;br /&gt;
==Overview==&lt;br /&gt;
&lt;br /&gt;
[https://genecode.org/ GENE] is a gyrokinetic turbulence code that simulates plasma behavior at very small scales comparable to the ion and electron gyroradius. The code was originally developed at the [https://www.ipp.mpg.de/ Max Planck Institute for Plasma Physics] in Garching, Germany, with the first version written by [https://www.ipp.mpg.de/4159541/jenko Frank Jenko] in 1999 [1].&lt;br /&gt;
&lt;br /&gt;
GENE is widely used in the international fusion research community and is considered one of the leading codes for plasma turbulence simulations. The code has been continuously developed by an international team of researchers and is designed to run on high-performance supercomputers.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Purpose and Applications===&lt;br /&gt;
&lt;br /&gt;
The main purpose of GENE is to understand and predict turbulent transport in fusion plasmas. Plasma turbulence is one of the key factors limiting energy confinement in magnetic fusion devices, which directly affects the performance and efficiency of potential fusion power plants. By simulating this turbulence, GENE helps researchers:&lt;br /&gt;
&lt;br /&gt;
* Predict energy confinement times in fusion experiments&lt;br /&gt;
* Understand heat and particle transport mechanisms&lt;br /&gt;
* Optimize plasma conditions for better performance&lt;br /&gt;
* Design future fusion devices including ITER&lt;br /&gt;
* Validate theoretical models against experimental data&lt;br /&gt;
&lt;br /&gt;
The code has been successfully validated against experimental measurements from major fusion devices including ASDEX Upgrade and has shown excellent agreement with multiple simultaneous plasma observables.&lt;br /&gt;
&lt;br /&gt;
==Physical Model==&lt;br /&gt;
&lt;br /&gt;
GENE is based on gyrokinetic theory, which describes plasma behavior on spatial scales comparable to particle gyroradii and on time scales much slower than the cyclotron frequency. This approach reduces the complexity of the full kinetic description while retaining the essential physics of plasma turbulence.&lt;br /&gt;
&lt;br /&gt;
===Gyrokinetic Equations===&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic model assumes that:&lt;br /&gt;
* The plasma is strongly magnetized&lt;br /&gt;
* Perpendicular spatial scales are comparable to the ion gyroradius&lt;br /&gt;
* Frequencies are much lower than the ion cyclotron frequency&lt;br /&gt;
* Perturbations are small compared to background quantities&lt;br /&gt;
&lt;br /&gt;
The fundamental equations solved by GENE include:&lt;br /&gt;
&lt;br /&gt;
====Gyrokinetic Vlasov Equation====&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic equation describes the evolution of the perturbed distribution function. In simplified form, it can be written as:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\frac{\partial h_s}{\partial t} + \mathbf{v}_{\text{gc}} \cdot \nabla h_s + \dot{v}_\parallel \frac{\partial h_s}{\partial v_\parallel} = C(h_s)&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
where:&lt;br /&gt;
* &amp;lt;math&amp;gt;h_s&amp;lt;/math&amp;gt; is the perturbed distribution function for species &#039;&#039;s&#039;&#039;&lt;br /&gt;
* &amp;lt;math&amp;gt;\mathbf{v}_{\text{gc}}&amp;lt;/math&amp;gt; is the guiding center velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;v_\parallel&amp;lt;/math&amp;gt; is the parallel velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;C(h_s)&amp;lt;/math&amp;gt; represents collisional effects&lt;br /&gt;
&lt;br /&gt;
====Maxwell&#039;s Equations====&lt;br /&gt;
&lt;br /&gt;
GENE couples the gyrokinetic equation to Maxwell&#039;s equations to determine the electromagnetic fields. In the electrostatic approximation, this reduces to the quasineutrality condition:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\sum_s Z_s e B \int dv_\parallel \, d\mu \, d\varphi \, h_s(\mathbf{R}) = \sum_s \frac{Z_s^2 e^2 n_s \phi}{T_s}&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
For electromagnetic simulations, GENE also solves Ampère&#039;s law for the parallel magnetic field perturbations.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Turbulence Mechanisms===&lt;br /&gt;
&lt;br /&gt;
GENE can simulate various types of plasma turbulence, including:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Ion Temperature Gradient (ITG) modes&#039;&#039;&#039; - driven by temperature gradients in the plasma&lt;br /&gt;
* &#039;&#039;&#039;Trapped Electron Modes (TEM)&#039;&#039;&#039; - caused by particles trapped in magnetic field variations&lt;br /&gt;
* &#039;&#039;&#039;Electron Temperature Gradient (ETG) modes&#039;&#039;&#039; - electron-scale turbulence&lt;br /&gt;
* &#039;&#039;&#039;Kinetic Ballooning Modes (KBM)&#039;&#039;&#039; - pressure-driven instabilities&lt;br /&gt;
* &#039;&#039;&#039;Microtearing modes&#039;&#039;&#039; - electromagnetic instabilities that can tear magnetic field lines&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Numerical Methods==&lt;br /&gt;
&lt;br /&gt;
GENE is a Eulerian code, meaning it solves the gyrokinetic equations on a fixed grid in phase space rather than following individual particles. This approach has several advantages for turbulence simulations.&lt;br /&gt;
&lt;br /&gt;
===Discretization===&lt;br /&gt;
&lt;br /&gt;
The code uses a combination of numerical methods:&lt;br /&gt;
* &#039;&#039;&#039;Spectral methods&#039;&#039;&#039; in the perpendicular directions (for periodic boundary conditions)&lt;br /&gt;
* &#039;&#039;&#039;Finite differences&#039;&#039;&#039; in the radial direction (for global simulations)&lt;br /&gt;
* &#039;&#039;&#039;Upwind schemes&#039;&#039;&#039; along magnetic field lines&lt;br /&gt;
* &#039;&#039;&#039;Runge-Kutta methods&#039;&#039;&#039; for time integration&lt;br /&gt;
&lt;br /&gt;
===Coordinate Systems===&lt;br /&gt;
&lt;br /&gt;
GENE employs field-aligned coordinates that follow magnetic field lines, which is natural for strongly magnetized plasmas. Different versions of the code use different coordinate approaches:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Standard GENE&#039;&#039;&#039; - uses flux-tube or radially global geometry in tokamaks&lt;br /&gt;
* &#039;&#039;&#039;GENE-3D&#039;&#039;&#039; - full three-dimensional geometry for stellarators&lt;br /&gt;
* &#039;&#039;&#039;GENE-X&#039;&#039;&#039; - flux-coordinate independent (FCI) approach for edge and scrape-off layer regions&lt;br /&gt;
&lt;br /&gt;
==Code Versions and Extensions==&lt;br /&gt;
&lt;br /&gt;
===Local and Global Versions===&lt;br /&gt;
&lt;br /&gt;
GENE can operate in different spatial modes:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Local (flux-tube)&#039;&#039;&#039; - simulates a small radial region with periodic boundary conditions; computationally efficient for core turbulence&lt;br /&gt;
* &#039;&#039;&#039;Radially global&#039;&#039;&#039; - includes variations across the plasma radius; necessary for edge effects and profile evolution&lt;br /&gt;
&lt;br /&gt;
===GENE-3D===&lt;br /&gt;
&lt;br /&gt;
GENE-3D is an extension that handles the complex three-dimensional geometry of stellarators. Development of GENE-3D took approximately five years and was presented by Maurice Maurer and colleagues.[3] Unlike the original tokamak-oriented version, GENE-3D can simulate the full ion and electron dynamics in the complex magnetic field geometry of stellarators like Wendelstein 7-X.&lt;br /&gt;
&lt;br /&gt;
===GENE-X===&lt;br /&gt;
&lt;br /&gt;
GENE-X is a full-f gyrokinetic continuum code based on the flux-coordinate independent (FCI) approach.[4] This version was developed specifically to handle:&lt;br /&gt;
&lt;br /&gt;
* Edge and scrape-off layer turbulence&lt;br /&gt;
* Regions with magnetic X-points (where traditional field-aligned coordinates have singularities)&lt;br /&gt;
* Geometries without well-defined flux surfaces&lt;br /&gt;
* Transition regions between core and edge plasma&lt;br /&gt;
&lt;br /&gt;
GENE-X uses unstructured, locally Cartesian grids that provide flexibility while maintaining computational efficiency. The code is capable of simulating regions from the magnetic axis, across the separatrix, and into the scrape-off layer.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Development and Community==&lt;br /&gt;
&lt;br /&gt;
===History===&lt;br /&gt;
&lt;br /&gt;
Frank Jenko wrote the first version of GENE in 1999 during his early postdoctoral work[1]. Since then, the code has been continuously developed and improved by an international team of researchers. Major development centers include:&lt;br /&gt;
&lt;br /&gt;
* Max Planck Institute for Plasma Physics (IPP), Garching, Germany&lt;br /&gt;
* Max Planck Computing and Data Facility (MPCDF), Germany&lt;br /&gt;
* Technical University of Munich, Germany&lt;br /&gt;
* University of Texas at Austin, USA&lt;br /&gt;
* École Polytechnique Fédérale de Lausanne (EPFL), Switzerland&lt;br /&gt;
* Many other international institutions&lt;br /&gt;
&lt;br /&gt;
===International Collaboration===&lt;br /&gt;
&lt;br /&gt;
The GENE Development Team is an international collaboration that includes members from universities and research laboratories across the world. The project welcomes contributions from the global fusion community and maintains an open-source development model.&lt;br /&gt;
&lt;br /&gt;
Institutions using GENE include research centers in Germany, USA, Switzerland, France, UK, Netherlands, Italy, Japan, India, China, South Korea, and many others.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===High-Performance Computing===&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
GENE has been at the forefront of high-performance computing in plasma physics since the 1960s. The code is designed to run efficiently on the world&#039;s largest supercomputers. In 2022, a major project was launched with €2.14 million in EU funding to develop an exascale version of GENE, pioneering the transition to exascale supercomputers.[5]&lt;br /&gt;
&lt;br /&gt;
The goal is to create &amp;quot;digital twins&amp;quot; of fusion experiments like ITER, allowing researchers to predict plasma behavior rather than just interpret experimental results.&lt;br /&gt;
&lt;br /&gt;
==Validation and Impact==&lt;br /&gt;
&lt;br /&gt;
GENE has been extensively validated against experimental measurements from major fusion devices. A landmark 2025 study demonstrated successful multi-channel validation of GENE against ASDEX Upgrade tokamak data, comparing simultaneous measurements of multiple plasma properties including turbulence amplitudes, wavenumber spectra, and cross phases.[2]&lt;br /&gt;
&lt;br /&gt;
The code has been used to:&lt;br /&gt;
* Explain turbulence suppression by fast ions in tokamak plasmas&lt;br /&gt;
* Predict similar effects in stellarators&lt;br /&gt;
* Understand energy confinement scaling&lt;br /&gt;
* Design optimal plasma scenarios for ITER&lt;br /&gt;
* Investigate the effects of different wall materials (like tungsten) on plasma performance&lt;br /&gt;
&lt;br /&gt;
==See also==&lt;br /&gt;
&lt;br /&gt;
* [[Gyrokinetics]]&lt;br /&gt;
* [[Plasma (physics)]]&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Tokamak]]&lt;br /&gt;
* [[Stellarator]]&lt;br /&gt;
* [[ITER]]&lt;br /&gt;
* [[Max Planck Institute for Plasma Physics]]&lt;br /&gt;
* [[Computational plasma physics]]&lt;br /&gt;
* [[Magnetohydrodynamics]]&lt;br /&gt;
&lt;br /&gt;
==References==&lt;br /&gt;
&lt;br /&gt;
# Jenko, F. (1999). &amp;quot;Development of GENE code&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/5295353/06_22&lt;br /&gt;
# &amp;quot;Milestone in predicting core plasma turbulence: successful multi-channel validation of the gyrokinetic code GENE&amp;quot; (2025). Nature Communications. https://www.nature.com/articles/s41467-025-56997-2&lt;br /&gt;
# Maurer, M. et al. &amp;quot;Promising computer simulations for stellarator plasmas&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/4928395/05_20&lt;br /&gt;
# &amp;quot;GENE-X: A full-f gyrokinetic turbulence code based on the flux-coordinate independent approach&amp;quot; (2021). Computer Physics Communications. https://www.sciencedirect.com/science/article/abs/pii/S0010465521000989&lt;br /&gt;
# &amp;quot;Nuclear fusion simulation to pioneer transition to exascale supercomputers&amp;quot; (2023). EUROfusion. Retrieved from https://euro-fusion.org/member-news/nuclear-fusion-simulation-to-pioneer-transition-to-exascale-supercomputers/&lt;br /&gt;
&lt;br /&gt;
==External links==&lt;br /&gt;
&lt;br /&gt;
* [https://genecode.org Official GENE website]&lt;br /&gt;
* [https://www.ipp.mpg.de Max Planck Institute for Plasma Physics]&lt;br /&gt;
* [https://github.com/genestrucutretest/GENE GENE on GitHub] (if available)&lt;br /&gt;
* [https://www.iter.org ITER Organization]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Category:Plasma physics]]&lt;br /&gt;
[[Category:Nuclear fusion]]&lt;br /&gt;
[[Category:Computational physics]]&lt;br /&gt;
[[Category:Scientific simulation software]]&lt;br /&gt;
[[Category:Physics software]]&lt;br /&gt;
[[Category:Free science software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8548</id>
		<title>GENE</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8548"/>
		<updated>2026-02-09T21:54:41Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* Overview */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&#039;&#039;&#039;GENE&#039;&#039;&#039; (&#039;&#039;&#039;Gyrokinetic Electromagnetic Numerical Experiment&#039;&#039;&#039;) is an open-source computer simulation code used to study plasma turbulence in magnetic confinement fusion devices. GENE solves the gyrokinetic equations to simulate electromagnetic turbulence in plasmas, which is critical for understanding energy confinement in fusion reactors like tokamaks and stellarators.&lt;br /&gt;
&lt;br /&gt;
==Overview==&lt;br /&gt;
&lt;br /&gt;
GENE is a gyrokinetic turbulence code that simulates plasma behavior at very small scales comparable to the ion and electron gyroradius. The code was originally developed at the [https://www.ipp.mpg.de/ Max Planck Institute for Plasma Physics] in Garching, Germany, with the first version written by [https://www.ipp.mpg.de/4159541/jenko Frank Jenko] in 1999 [1].&lt;br /&gt;
&lt;br /&gt;
GENE is widely used in the international fusion research community and is considered one of the leading codes for plasma turbulence simulations. The code has been continuously developed by an international team of researchers and is designed to run on high-performance supercomputers.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Purpose and Applications===&lt;br /&gt;
&lt;br /&gt;
The main purpose of GENE is to understand and predict turbulent transport in fusion plasmas. Plasma turbulence is one of the key factors limiting energy confinement in magnetic fusion devices, which directly affects the performance and efficiency of potential fusion power plants. By simulating this turbulence, GENE helps researchers:&lt;br /&gt;
&lt;br /&gt;
* Predict energy confinement times in fusion experiments&lt;br /&gt;
* Understand heat and particle transport mechanisms&lt;br /&gt;
* Optimize plasma conditions for better performance&lt;br /&gt;
* Design future fusion devices including ITER&lt;br /&gt;
* Validate theoretical models against experimental data&lt;br /&gt;
&lt;br /&gt;
The code has been successfully validated against experimental measurements from major fusion devices including ASDEX Upgrade and has shown excellent agreement with multiple simultaneous plasma observables.&lt;br /&gt;
&lt;br /&gt;
==Physical Model==&lt;br /&gt;
&lt;br /&gt;
GENE is based on gyrokinetic theory, which describes plasma behavior on spatial scales comparable to particle gyroradii and on time scales much slower than the cyclotron frequency. This approach reduces the complexity of the full kinetic description while retaining the essential physics of plasma turbulence.&lt;br /&gt;
&lt;br /&gt;
===Gyrokinetic Equations===&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic model assumes that:&lt;br /&gt;
* The plasma is strongly magnetized&lt;br /&gt;
* Perpendicular spatial scales are comparable to the ion gyroradius&lt;br /&gt;
* Frequencies are much lower than the ion cyclotron frequency&lt;br /&gt;
* Perturbations are small compared to background quantities&lt;br /&gt;
&lt;br /&gt;
The fundamental equations solved by GENE include:&lt;br /&gt;
&lt;br /&gt;
====Gyrokinetic Vlasov Equation====&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic equation describes the evolution of the perturbed distribution function. In simplified form, it can be written as:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\frac{\partial h_s}{\partial t} + \mathbf{v}_{\text{gc}} \cdot \nabla h_s + \dot{v}_\parallel \frac{\partial h_s}{\partial v_\parallel} = C(h_s)&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
where:&lt;br /&gt;
* &amp;lt;math&amp;gt;h_s&amp;lt;/math&amp;gt; is the perturbed distribution function for species &#039;&#039;s&#039;&#039;&lt;br /&gt;
* &amp;lt;math&amp;gt;\mathbf{v}_{\text{gc}}&amp;lt;/math&amp;gt; is the guiding center velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;v_\parallel&amp;lt;/math&amp;gt; is the parallel velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;C(h_s)&amp;lt;/math&amp;gt; represents collisional effects&lt;br /&gt;
&lt;br /&gt;
====Maxwell&#039;s Equations====&lt;br /&gt;
&lt;br /&gt;
GENE couples the gyrokinetic equation to Maxwell&#039;s equations to determine the electromagnetic fields. In the electrostatic approximation, this reduces to the quasineutrality condition:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\sum_s Z_s e B \int dv_\parallel \, d\mu \, d\varphi \, h_s(\mathbf{R}) = \sum_s \frac{Z_s^2 e^2 n_s \phi}{T_s}&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
For electromagnetic simulations, GENE also solves Ampère&#039;s law for the parallel magnetic field perturbations.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Turbulence Mechanisms===&lt;br /&gt;
&lt;br /&gt;
GENE can simulate various types of plasma turbulence, including:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Ion Temperature Gradient (ITG) modes&#039;&#039;&#039; - driven by temperature gradients in the plasma&lt;br /&gt;
* &#039;&#039;&#039;Trapped Electron Modes (TEM)&#039;&#039;&#039; - caused by particles trapped in magnetic field variations&lt;br /&gt;
* &#039;&#039;&#039;Electron Temperature Gradient (ETG) modes&#039;&#039;&#039; - electron-scale turbulence&lt;br /&gt;
* &#039;&#039;&#039;Kinetic Ballooning Modes (KBM)&#039;&#039;&#039; - pressure-driven instabilities&lt;br /&gt;
* &#039;&#039;&#039;Microtearing modes&#039;&#039;&#039; - electromagnetic instabilities that can tear magnetic field lines&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Numerical Methods==&lt;br /&gt;
&lt;br /&gt;
GENE is a Eulerian code, meaning it solves the gyrokinetic equations on a fixed grid in phase space rather than following individual particles. This approach has several advantages for turbulence simulations.&lt;br /&gt;
&lt;br /&gt;
===Discretization===&lt;br /&gt;
&lt;br /&gt;
The code uses a combination of numerical methods:&lt;br /&gt;
* &#039;&#039;&#039;Spectral methods&#039;&#039;&#039; in the perpendicular directions (for periodic boundary conditions)&lt;br /&gt;
* &#039;&#039;&#039;Finite differences&#039;&#039;&#039; in the radial direction (for global simulations)&lt;br /&gt;
* &#039;&#039;&#039;Upwind schemes&#039;&#039;&#039; along magnetic field lines&lt;br /&gt;
* &#039;&#039;&#039;Runge-Kutta methods&#039;&#039;&#039; for time integration&lt;br /&gt;
&lt;br /&gt;
===Coordinate Systems===&lt;br /&gt;
&lt;br /&gt;
GENE employs field-aligned coordinates that follow magnetic field lines, which is natural for strongly magnetized plasmas. Different versions of the code use different coordinate approaches:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Standard GENE&#039;&#039;&#039; - uses flux-tube or radially global geometry in tokamaks&lt;br /&gt;
* &#039;&#039;&#039;GENE-3D&#039;&#039;&#039; - full three-dimensional geometry for stellarators&lt;br /&gt;
* &#039;&#039;&#039;GENE-X&#039;&#039;&#039; - flux-coordinate independent (FCI) approach for edge and scrape-off layer regions&lt;br /&gt;
&lt;br /&gt;
==Code Versions and Extensions==&lt;br /&gt;
&lt;br /&gt;
===Local and Global Versions===&lt;br /&gt;
&lt;br /&gt;
GENE can operate in different spatial modes:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Local (flux-tube)&#039;&#039;&#039; - simulates a small radial region with periodic boundary conditions; computationally efficient for core turbulence&lt;br /&gt;
* &#039;&#039;&#039;Radially global&#039;&#039;&#039; - includes variations across the plasma radius; necessary for edge effects and profile evolution&lt;br /&gt;
&lt;br /&gt;
===GENE-3D===&lt;br /&gt;
&lt;br /&gt;
GENE-3D is an extension that handles the complex three-dimensional geometry of stellarators. Development of GENE-3D took approximately five years and was presented by Maurice Maurer and colleagues.[3] Unlike the original tokamak-oriented version, GENE-3D can simulate the full ion and electron dynamics in the complex magnetic field geometry of stellarators like Wendelstein 7-X.&lt;br /&gt;
&lt;br /&gt;
===GENE-X===&lt;br /&gt;
&lt;br /&gt;
GENE-X is a full-f gyrokinetic continuum code based on the flux-coordinate independent (FCI) approach.[4] This version was developed specifically to handle:&lt;br /&gt;
&lt;br /&gt;
* Edge and scrape-off layer turbulence&lt;br /&gt;
* Regions with magnetic X-points (where traditional field-aligned coordinates have singularities)&lt;br /&gt;
* Geometries without well-defined flux surfaces&lt;br /&gt;
* Transition regions between core and edge plasma&lt;br /&gt;
&lt;br /&gt;
GENE-X uses unstructured, locally Cartesian grids that provide flexibility while maintaining computational efficiency. The code is capable of simulating regions from the magnetic axis, across the separatrix, and into the scrape-off layer.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Development and Community==&lt;br /&gt;
&lt;br /&gt;
===History===&lt;br /&gt;
&lt;br /&gt;
Frank Jenko wrote the first version of GENE in 1999 during his early postdoctoral work.[1] Since then, the code has been continuously developed and improved by an international team of researchers. Major development centers include:&lt;br /&gt;
&lt;br /&gt;
* Max Planck Institute for Plasma Physics (IPP), Garching, Germany&lt;br /&gt;
* Max Planck Computing and Data Facility (MPCDF), Germany&lt;br /&gt;
* Technical University of Munich, Germany&lt;br /&gt;
* University of Texas at Austin, USA&lt;br /&gt;
* École Polytechnique Fédérale de Lausanne (EPFL), Switzerland&lt;br /&gt;
* Many other international institutions&lt;br /&gt;
&lt;br /&gt;
===International Collaboration===&lt;br /&gt;
&lt;br /&gt;
The GENE Development Team is an international collaboration that includes members from universities and research laboratories across the world. The project welcomes contributions from the global fusion community and maintains an open-source development model.&lt;br /&gt;
&lt;br /&gt;
Institutions using GENE include research centers in Germany, USA, Switzerland, France, UK, Netherlands, Italy, Japan, India, China, South Korea, and many others.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===High-Performance Computing===&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
GENE has been at the forefront of high-performance computing in plasma physics since the 1960s. The code is designed to run efficiently on the world&#039;s largest supercomputers. In 2022, a major project was launched with €2.14 million in EU funding to develop an exascale version of GENE, pioneering the transition to exascale supercomputers.[5]&lt;br /&gt;
&lt;br /&gt;
The goal is to create &amp;quot;digital twins&amp;quot; of fusion experiments like ITER, allowing researchers to predict plasma behavior rather than just interpret experimental results.&lt;br /&gt;
&lt;br /&gt;
==Validation and Impact==&lt;br /&gt;
&lt;br /&gt;
GENE has been extensively validated against experimental measurements from major fusion devices. A landmark 2025 study demonstrated successful multi-channel validation of GENE against ASDEX Upgrade tokamak data, comparing simultaneous measurements of multiple plasma properties including turbulence amplitudes, wavenumber spectra, and cross phases.[2]&lt;br /&gt;
&lt;br /&gt;
The code has been used to:&lt;br /&gt;
* Explain turbulence suppression by fast ions in tokamak plasmas&lt;br /&gt;
* Predict similar effects in stellarators&lt;br /&gt;
* Understand energy confinement scaling&lt;br /&gt;
* Design optimal plasma scenarios for ITER&lt;br /&gt;
* Investigate the effects of different wall materials (like tungsten) on plasma performance&lt;br /&gt;
&lt;br /&gt;
==See also==&lt;br /&gt;
&lt;br /&gt;
* [[Gyrokinetics]]&lt;br /&gt;
* [[Plasma (physics)]]&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Tokamak]]&lt;br /&gt;
* [[Stellarator]]&lt;br /&gt;
* [[ITER]]&lt;br /&gt;
* [[Max Planck Institute for Plasma Physics]]&lt;br /&gt;
* [[Computational plasma physics]]&lt;br /&gt;
* [[Magnetohydrodynamics]]&lt;br /&gt;
&lt;br /&gt;
==References==&lt;br /&gt;
&lt;br /&gt;
# Jenko, F. (1999). &amp;quot;Development of GENE code&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/5295353/06_22&lt;br /&gt;
# &amp;quot;Milestone in predicting core plasma turbulence: successful multi-channel validation of the gyrokinetic code GENE&amp;quot; (2025). Nature Communications. https://www.nature.com/articles/s41467-025-56997-2&lt;br /&gt;
# Maurer, M. et al. &amp;quot;Promising computer simulations for stellarator plasmas&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/4928395/05_20&lt;br /&gt;
# &amp;quot;GENE-X: A full-f gyrokinetic turbulence code based on the flux-coordinate independent approach&amp;quot; (2021). Computer Physics Communications. https://www.sciencedirect.com/science/article/abs/pii/S0010465521000989&lt;br /&gt;
# &amp;quot;Nuclear fusion simulation to pioneer transition to exascale supercomputers&amp;quot; (2023). EUROfusion. Retrieved from https://euro-fusion.org/member-news/nuclear-fusion-simulation-to-pioneer-transition-to-exascale-supercomputers/&lt;br /&gt;
&lt;br /&gt;
==External links==&lt;br /&gt;
&lt;br /&gt;
* [https://genecode.org Official GENE website]&lt;br /&gt;
* [https://www.ipp.mpg.de Max Planck Institute for Plasma Physics]&lt;br /&gt;
* [https://github.com/genestrucutretest/GENE GENE on GitHub] (if available)&lt;br /&gt;
* [https://www.iter.org ITER Organization]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Category:Plasma physics]]&lt;br /&gt;
[[Category:Nuclear fusion]]&lt;br /&gt;
[[Category:Computational physics]]&lt;br /&gt;
[[Category:Scientific simulation software]]&lt;br /&gt;
[[Category:Physics software]]&lt;br /&gt;
[[Category:Free science software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8547</id>
		<title>GENE</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8547"/>
		<updated>2026-02-09T21:53:12Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* Overview */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&#039;&#039;&#039;GENE&#039;&#039;&#039; (&#039;&#039;&#039;Gyrokinetic Electromagnetic Numerical Experiment&#039;&#039;&#039;) is an open-source computer simulation code used to study plasma turbulence in magnetic confinement fusion devices. GENE solves the gyrokinetic equations to simulate electromagnetic turbulence in plasmas, which is critical for understanding energy confinement in fusion reactors like tokamaks and stellarators.&lt;br /&gt;
&lt;br /&gt;
==Overview==&lt;br /&gt;
&lt;br /&gt;
GENE is a gyrokinetic turbulence code that simulates plasma behavior at very small scales comparable to the ion and electron gyroradius. The code was originally developed at the [https://www.ipp.mpg.de/ Max Planck Institute for Plasma Physics] in Garching, Germany, with the first version written by Frank Jenko in 1999 [1].&lt;br /&gt;
&lt;br /&gt;
GENE is widely used in the international fusion research community and is considered one of the leading codes for plasma turbulence simulations. The code has been continuously developed by an international team of researchers and is designed to run on high-performance supercomputers.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Purpose and Applications===&lt;br /&gt;
&lt;br /&gt;
The main purpose of GENE is to understand and predict turbulent transport in fusion plasmas. Plasma turbulence is one of the key factors limiting energy confinement in magnetic fusion devices, which directly affects the performance and efficiency of potential fusion power plants. By simulating this turbulence, GENE helps researchers:&lt;br /&gt;
&lt;br /&gt;
* Predict energy confinement times in fusion experiments&lt;br /&gt;
* Understand heat and particle transport mechanisms&lt;br /&gt;
* Optimize plasma conditions for better performance&lt;br /&gt;
* Design future fusion devices including ITER&lt;br /&gt;
* Validate theoretical models against experimental data&lt;br /&gt;
&lt;br /&gt;
The code has been successfully validated against experimental measurements from major fusion devices including ASDEX Upgrade and has shown excellent agreement with multiple simultaneous plasma observables.&lt;br /&gt;
&lt;br /&gt;
==Physical Model==&lt;br /&gt;
&lt;br /&gt;
GENE is based on gyrokinetic theory, which describes plasma behavior on spatial scales comparable to particle gyroradii and on time scales much slower than the cyclotron frequency. This approach reduces the complexity of the full kinetic description while retaining the essential physics of plasma turbulence.&lt;br /&gt;
&lt;br /&gt;
===Gyrokinetic Equations===&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic model assumes that:&lt;br /&gt;
* The plasma is strongly magnetized&lt;br /&gt;
* Perpendicular spatial scales are comparable to the ion gyroradius&lt;br /&gt;
* Frequencies are much lower than the ion cyclotron frequency&lt;br /&gt;
* Perturbations are small compared to background quantities&lt;br /&gt;
&lt;br /&gt;
The fundamental equations solved by GENE include:&lt;br /&gt;
&lt;br /&gt;
====Gyrokinetic Vlasov Equation====&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic equation describes the evolution of the perturbed distribution function. In simplified form, it can be written as:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\frac{\partial h_s}{\partial t} + \mathbf{v}_{\text{gc}} \cdot \nabla h_s + \dot{v}_\parallel \frac{\partial h_s}{\partial v_\parallel} = C(h_s)&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
where:&lt;br /&gt;
* &amp;lt;math&amp;gt;h_s&amp;lt;/math&amp;gt; is the perturbed distribution function for species &#039;&#039;s&#039;&#039;&lt;br /&gt;
* &amp;lt;math&amp;gt;\mathbf{v}_{\text{gc}}&amp;lt;/math&amp;gt; is the guiding center velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;v_\parallel&amp;lt;/math&amp;gt; is the parallel velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;C(h_s)&amp;lt;/math&amp;gt; represents collisional effects&lt;br /&gt;
&lt;br /&gt;
====Maxwell&#039;s Equations====&lt;br /&gt;
&lt;br /&gt;
GENE couples the gyrokinetic equation to Maxwell&#039;s equations to determine the electromagnetic fields. In the electrostatic approximation, this reduces to the quasineutrality condition:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\sum_s Z_s e B \int dv_\parallel \, d\mu \, d\varphi \, h_s(\mathbf{R}) = \sum_s \frac{Z_s^2 e^2 n_s \phi}{T_s}&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
For electromagnetic simulations, GENE also solves Ampère&#039;s law for the parallel magnetic field perturbations.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Turbulence Mechanisms===&lt;br /&gt;
&lt;br /&gt;
GENE can simulate various types of plasma turbulence, including:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Ion Temperature Gradient (ITG) modes&#039;&#039;&#039; - driven by temperature gradients in the plasma&lt;br /&gt;
* &#039;&#039;&#039;Trapped Electron Modes (TEM)&#039;&#039;&#039; - caused by particles trapped in magnetic field variations&lt;br /&gt;
* &#039;&#039;&#039;Electron Temperature Gradient (ETG) modes&#039;&#039;&#039; - electron-scale turbulence&lt;br /&gt;
* &#039;&#039;&#039;Kinetic Ballooning Modes (KBM)&#039;&#039;&#039; - pressure-driven instabilities&lt;br /&gt;
* &#039;&#039;&#039;Microtearing modes&#039;&#039;&#039; - electromagnetic instabilities that can tear magnetic field lines&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Numerical Methods==&lt;br /&gt;
&lt;br /&gt;
GENE is a Eulerian code, meaning it solves the gyrokinetic equations on a fixed grid in phase space rather than following individual particles. This approach has several advantages for turbulence simulations.&lt;br /&gt;
&lt;br /&gt;
===Discretization===&lt;br /&gt;
&lt;br /&gt;
The code uses a combination of numerical methods:&lt;br /&gt;
* &#039;&#039;&#039;Spectral methods&#039;&#039;&#039; in the perpendicular directions (for periodic boundary conditions)&lt;br /&gt;
* &#039;&#039;&#039;Finite differences&#039;&#039;&#039; in the radial direction (for global simulations)&lt;br /&gt;
* &#039;&#039;&#039;Upwind schemes&#039;&#039;&#039; along magnetic field lines&lt;br /&gt;
* &#039;&#039;&#039;Runge-Kutta methods&#039;&#039;&#039; for time integration&lt;br /&gt;
&lt;br /&gt;
===Coordinate Systems===&lt;br /&gt;
&lt;br /&gt;
GENE employs field-aligned coordinates that follow magnetic field lines, which is natural for strongly magnetized plasmas. Different versions of the code use different coordinate approaches:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Standard GENE&#039;&#039;&#039; - uses flux-tube or radially global geometry in tokamaks&lt;br /&gt;
* &#039;&#039;&#039;GENE-3D&#039;&#039;&#039; - full three-dimensional geometry for stellarators&lt;br /&gt;
* &#039;&#039;&#039;GENE-X&#039;&#039;&#039; - flux-coordinate independent (FCI) approach for edge and scrape-off layer regions&lt;br /&gt;
&lt;br /&gt;
==Code Versions and Extensions==&lt;br /&gt;
&lt;br /&gt;
===Local and Global Versions===&lt;br /&gt;
&lt;br /&gt;
GENE can operate in different spatial modes:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Local (flux-tube)&#039;&#039;&#039; - simulates a small radial region with periodic boundary conditions; computationally efficient for core turbulence&lt;br /&gt;
* &#039;&#039;&#039;Radially global&#039;&#039;&#039; - includes variations across the plasma radius; necessary for edge effects and profile evolution&lt;br /&gt;
&lt;br /&gt;
===GENE-3D===&lt;br /&gt;
&lt;br /&gt;
GENE-3D is an extension that handles the complex three-dimensional geometry of stellarators. Development of GENE-3D took approximately five years and was presented by Maurice Maurer and colleagues.[3] Unlike the original tokamak-oriented version, GENE-3D can simulate the full ion and electron dynamics in the complex magnetic field geometry of stellarators like Wendelstein 7-X.&lt;br /&gt;
&lt;br /&gt;
===GENE-X===&lt;br /&gt;
&lt;br /&gt;
GENE-X is a full-f gyrokinetic continuum code based on the flux-coordinate independent (FCI) approach.[4] This version was developed specifically to handle:&lt;br /&gt;
&lt;br /&gt;
* Edge and scrape-off layer turbulence&lt;br /&gt;
* Regions with magnetic X-points (where traditional field-aligned coordinates have singularities)&lt;br /&gt;
* Geometries without well-defined flux surfaces&lt;br /&gt;
* Transition regions between core and edge plasma&lt;br /&gt;
&lt;br /&gt;
GENE-X uses unstructured, locally Cartesian grids that provide flexibility while maintaining computational efficiency. The code is capable of simulating regions from the magnetic axis, across the separatrix, and into the scrape-off layer.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Development and Community==&lt;br /&gt;
&lt;br /&gt;
===History===&lt;br /&gt;
&lt;br /&gt;
Frank Jenko wrote the first version of GENE in 1999 during his early postdoctoral work.[1] Since then, the code has been continuously developed and improved by an international team of researchers. Major development centers include:&lt;br /&gt;
&lt;br /&gt;
* Max Planck Institute for Plasma Physics (IPP), Garching, Germany&lt;br /&gt;
* Max Planck Computing and Data Facility (MPCDF), Germany&lt;br /&gt;
* Technical University of Munich, Germany&lt;br /&gt;
* University of Texas at Austin, USA&lt;br /&gt;
* École Polytechnique Fédérale de Lausanne (EPFL), Switzerland&lt;br /&gt;
* Many other international institutions&lt;br /&gt;
&lt;br /&gt;
===International Collaboration===&lt;br /&gt;
&lt;br /&gt;
The GENE Development Team is an international collaboration that includes members from universities and research laboratories across the world. The project welcomes contributions from the global fusion community and maintains an open-source development model.&lt;br /&gt;
&lt;br /&gt;
Institutions using GENE include research centers in Germany, USA, Switzerland, France, UK, Netherlands, Italy, Japan, India, China, South Korea, and many others.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===High-Performance Computing===&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
GENE has been at the forefront of high-performance computing in plasma physics since the 1960s. The code is designed to run efficiently on the world&#039;s largest supercomputers. In 2022, a major project was launched with €2.14 million in EU funding to develop an exascale version of GENE, pioneering the transition to exascale supercomputers.[5]&lt;br /&gt;
&lt;br /&gt;
The goal is to create &amp;quot;digital twins&amp;quot; of fusion experiments like ITER, allowing researchers to predict plasma behavior rather than just interpret experimental results.&lt;br /&gt;
&lt;br /&gt;
==Validation and Impact==&lt;br /&gt;
&lt;br /&gt;
GENE has been extensively validated against experimental measurements from major fusion devices. A landmark 2025 study demonstrated successful multi-channel validation of GENE against ASDEX Upgrade tokamak data, comparing simultaneous measurements of multiple plasma properties including turbulence amplitudes, wavenumber spectra, and cross phases.[2]&lt;br /&gt;
&lt;br /&gt;
The code has been used to:&lt;br /&gt;
* Explain turbulence suppression by fast ions in tokamak plasmas&lt;br /&gt;
* Predict similar effects in stellarators&lt;br /&gt;
* Understand energy confinement scaling&lt;br /&gt;
* Design optimal plasma scenarios for ITER&lt;br /&gt;
* Investigate the effects of different wall materials (like tungsten) on plasma performance&lt;br /&gt;
&lt;br /&gt;
==See also==&lt;br /&gt;
&lt;br /&gt;
* [[Gyrokinetics]]&lt;br /&gt;
* [[Plasma (physics)]]&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Tokamak]]&lt;br /&gt;
* [[Stellarator]]&lt;br /&gt;
* [[ITER]]&lt;br /&gt;
* [[Max Planck Institute for Plasma Physics]]&lt;br /&gt;
* [[Computational plasma physics]]&lt;br /&gt;
* [[Magnetohydrodynamics]]&lt;br /&gt;
&lt;br /&gt;
==References==&lt;br /&gt;
&lt;br /&gt;
# Jenko, F. (1999). &amp;quot;Development of GENE code&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/5295353/06_22&lt;br /&gt;
# &amp;quot;Milestone in predicting core plasma turbulence: successful multi-channel validation of the gyrokinetic code GENE&amp;quot; (2025). Nature Communications. https://www.nature.com/articles/s41467-025-56997-2&lt;br /&gt;
# Maurer, M. et al. &amp;quot;Promising computer simulations for stellarator plasmas&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/4928395/05_20&lt;br /&gt;
# &amp;quot;GENE-X: A full-f gyrokinetic turbulence code based on the flux-coordinate independent approach&amp;quot; (2021). Computer Physics Communications. https://www.sciencedirect.com/science/article/abs/pii/S0010465521000989&lt;br /&gt;
# &amp;quot;Nuclear fusion simulation to pioneer transition to exascale supercomputers&amp;quot; (2023). EUROfusion. Retrieved from https://euro-fusion.org/member-news/nuclear-fusion-simulation-to-pioneer-transition-to-exascale-supercomputers/&lt;br /&gt;
&lt;br /&gt;
==External links==&lt;br /&gt;
&lt;br /&gt;
* [https://genecode.org Official GENE website]&lt;br /&gt;
* [https://www.ipp.mpg.de Max Planck Institute for Plasma Physics]&lt;br /&gt;
* [https://github.com/genestrucutretest/GENE GENE on GitHub] (if available)&lt;br /&gt;
* [https://www.iter.org ITER Organization]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Category:Plasma physics]]&lt;br /&gt;
[[Category:Nuclear fusion]]&lt;br /&gt;
[[Category:Computational physics]]&lt;br /&gt;
[[Category:Scientific simulation software]]&lt;br /&gt;
[[Category:Physics software]]&lt;br /&gt;
[[Category:Free science software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8546</id>
		<title>GENE</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8546"/>
		<updated>2026-02-09T21:52:20Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* Overview */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&#039;&#039;&#039;GENE&#039;&#039;&#039; (&#039;&#039;&#039;Gyrokinetic Electromagnetic Numerical Experiment&#039;&#039;&#039;) is an open-source computer simulation code used to study plasma turbulence in magnetic confinement fusion devices. GENE solves the gyrokinetic equations to simulate electromagnetic turbulence in plasmas, which is critical for understanding energy confinement in fusion reactors like tokamaks and stellarators.&lt;br /&gt;
&lt;br /&gt;
==Overview==&lt;br /&gt;
&lt;br /&gt;
GENE is a gyrokinetic turbulence code that simulates plasma behavior at very small scales comparable to the ion and electron gyroradius. The code was originally developed at the [[Max Planck Institute for Plasma Physics|IPP Max Planck]] in Garching, Germany, with the first version written by Frank Jenko in 1999 [1].&lt;br /&gt;
&lt;br /&gt;
GENE is widely used in the international fusion research community and is considered one of the leading codes for plasma turbulence simulations. The code has been continuously developed by an international team of researchers and is designed to run on high-performance supercomputers.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Purpose and Applications===&lt;br /&gt;
&lt;br /&gt;
The main purpose of GENE is to understand and predict turbulent transport in fusion plasmas. Plasma turbulence is one of the key factors limiting energy confinement in magnetic fusion devices, which directly affects the performance and efficiency of potential fusion power plants. By simulating this turbulence, GENE helps researchers:&lt;br /&gt;
&lt;br /&gt;
* Predict energy confinement times in fusion experiments&lt;br /&gt;
* Understand heat and particle transport mechanisms&lt;br /&gt;
* Optimize plasma conditions for better performance&lt;br /&gt;
* Design future fusion devices including ITER&lt;br /&gt;
* Validate theoretical models against experimental data&lt;br /&gt;
&lt;br /&gt;
The code has been successfully validated against experimental measurements from major fusion devices including ASDEX Upgrade and has shown excellent agreement with multiple simultaneous plasma observables.&lt;br /&gt;
&lt;br /&gt;
==Physical Model==&lt;br /&gt;
&lt;br /&gt;
GENE is based on gyrokinetic theory, which describes plasma behavior on spatial scales comparable to particle gyroradii and on time scales much slower than the cyclotron frequency. This approach reduces the complexity of the full kinetic description while retaining the essential physics of plasma turbulence.&lt;br /&gt;
&lt;br /&gt;
===Gyrokinetic Equations===&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic model assumes that:&lt;br /&gt;
* The plasma is strongly magnetized&lt;br /&gt;
* Perpendicular spatial scales are comparable to the ion gyroradius&lt;br /&gt;
* Frequencies are much lower than the ion cyclotron frequency&lt;br /&gt;
* Perturbations are small compared to background quantities&lt;br /&gt;
&lt;br /&gt;
The fundamental equations solved by GENE include:&lt;br /&gt;
&lt;br /&gt;
====Gyrokinetic Vlasov Equation====&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic equation describes the evolution of the perturbed distribution function. In simplified form, it can be written as:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\frac{\partial h_s}{\partial t} + \mathbf{v}_{\text{gc}} \cdot \nabla h_s + \dot{v}_\parallel \frac{\partial h_s}{\partial v_\parallel} = C(h_s)&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
where:&lt;br /&gt;
* &amp;lt;math&amp;gt;h_s&amp;lt;/math&amp;gt; is the perturbed distribution function for species &#039;&#039;s&#039;&#039;&lt;br /&gt;
* &amp;lt;math&amp;gt;\mathbf{v}_{\text{gc}}&amp;lt;/math&amp;gt; is the guiding center velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;v_\parallel&amp;lt;/math&amp;gt; is the parallel velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;C(h_s)&amp;lt;/math&amp;gt; represents collisional effects&lt;br /&gt;
&lt;br /&gt;
====Maxwell&#039;s Equations====&lt;br /&gt;
&lt;br /&gt;
GENE couples the gyrokinetic equation to Maxwell&#039;s equations to determine the electromagnetic fields. In the electrostatic approximation, this reduces to the quasineutrality condition:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\sum_s Z_s e B \int dv_\parallel \, d\mu \, d\varphi \, h_s(\mathbf{R}) = \sum_s \frac{Z_s^2 e^2 n_s \phi}{T_s}&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
For electromagnetic simulations, GENE also solves Ampère&#039;s law for the parallel magnetic field perturbations.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Turbulence Mechanisms===&lt;br /&gt;
&lt;br /&gt;
GENE can simulate various types of plasma turbulence, including:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Ion Temperature Gradient (ITG) modes&#039;&#039;&#039; - driven by temperature gradients in the plasma&lt;br /&gt;
* &#039;&#039;&#039;Trapped Electron Modes (TEM)&#039;&#039;&#039; - caused by particles trapped in magnetic field variations&lt;br /&gt;
* &#039;&#039;&#039;Electron Temperature Gradient (ETG) modes&#039;&#039;&#039; - electron-scale turbulence&lt;br /&gt;
* &#039;&#039;&#039;Kinetic Ballooning Modes (KBM)&#039;&#039;&#039; - pressure-driven instabilities&lt;br /&gt;
* &#039;&#039;&#039;Microtearing modes&#039;&#039;&#039; - electromagnetic instabilities that can tear magnetic field lines&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Numerical Methods==&lt;br /&gt;
&lt;br /&gt;
GENE is a Eulerian code, meaning it solves the gyrokinetic equations on a fixed grid in phase space rather than following individual particles. This approach has several advantages for turbulence simulations.&lt;br /&gt;
&lt;br /&gt;
===Discretization===&lt;br /&gt;
&lt;br /&gt;
The code uses a combination of numerical methods:&lt;br /&gt;
* &#039;&#039;&#039;Spectral methods&#039;&#039;&#039; in the perpendicular directions (for periodic boundary conditions)&lt;br /&gt;
* &#039;&#039;&#039;Finite differences&#039;&#039;&#039; in the radial direction (for global simulations)&lt;br /&gt;
* &#039;&#039;&#039;Upwind schemes&#039;&#039;&#039; along magnetic field lines&lt;br /&gt;
* &#039;&#039;&#039;Runge-Kutta methods&#039;&#039;&#039; for time integration&lt;br /&gt;
&lt;br /&gt;
===Coordinate Systems===&lt;br /&gt;
&lt;br /&gt;
GENE employs field-aligned coordinates that follow magnetic field lines, which is natural for strongly magnetized plasmas. Different versions of the code use different coordinate approaches:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Standard GENE&#039;&#039;&#039; - uses flux-tube or radially global geometry in tokamaks&lt;br /&gt;
* &#039;&#039;&#039;GENE-3D&#039;&#039;&#039; - full three-dimensional geometry for stellarators&lt;br /&gt;
* &#039;&#039;&#039;GENE-X&#039;&#039;&#039; - flux-coordinate independent (FCI) approach for edge and scrape-off layer regions&lt;br /&gt;
&lt;br /&gt;
==Code Versions and Extensions==&lt;br /&gt;
&lt;br /&gt;
===Local and Global Versions===&lt;br /&gt;
&lt;br /&gt;
GENE can operate in different spatial modes:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Local (flux-tube)&#039;&#039;&#039; - simulates a small radial region with periodic boundary conditions; computationally efficient for core turbulence&lt;br /&gt;
* &#039;&#039;&#039;Radially global&#039;&#039;&#039; - includes variations across the plasma radius; necessary for edge effects and profile evolution&lt;br /&gt;
&lt;br /&gt;
===GENE-3D===&lt;br /&gt;
&lt;br /&gt;
GENE-3D is an extension that handles the complex three-dimensional geometry of stellarators. Development of GENE-3D took approximately five years and was presented by Maurice Maurer and colleagues.[3] Unlike the original tokamak-oriented version, GENE-3D can simulate the full ion and electron dynamics in the complex magnetic field geometry of stellarators like Wendelstein 7-X.&lt;br /&gt;
&lt;br /&gt;
===GENE-X===&lt;br /&gt;
&lt;br /&gt;
GENE-X is a full-f gyrokinetic continuum code based on the flux-coordinate independent (FCI) approach.[4] This version was developed specifically to handle:&lt;br /&gt;
&lt;br /&gt;
* Edge and scrape-off layer turbulence&lt;br /&gt;
* Regions with magnetic X-points (where traditional field-aligned coordinates have singularities)&lt;br /&gt;
* Geometries without well-defined flux surfaces&lt;br /&gt;
* Transition regions between core and edge plasma&lt;br /&gt;
&lt;br /&gt;
GENE-X uses unstructured, locally Cartesian grids that provide flexibility while maintaining computational efficiency. The code is capable of simulating regions from the magnetic axis, across the separatrix, and into the scrape-off layer.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Development and Community==&lt;br /&gt;
&lt;br /&gt;
===History===&lt;br /&gt;
&lt;br /&gt;
Frank Jenko wrote the first version of GENE in 1999 during his early postdoctoral work.[1] Since then, the code has been continuously developed and improved by an international team of researchers. Major development centers include:&lt;br /&gt;
&lt;br /&gt;
* Max Planck Institute for Plasma Physics (IPP), Garching, Germany&lt;br /&gt;
* Max Planck Computing and Data Facility (MPCDF), Germany&lt;br /&gt;
* Technical University of Munich, Germany&lt;br /&gt;
* University of Texas at Austin, USA&lt;br /&gt;
* École Polytechnique Fédérale de Lausanne (EPFL), Switzerland&lt;br /&gt;
* Many other international institutions&lt;br /&gt;
&lt;br /&gt;
===International Collaboration===&lt;br /&gt;
&lt;br /&gt;
The GENE Development Team is an international collaboration that includes members from universities and research laboratories across the world. The project welcomes contributions from the global fusion community and maintains an open-source development model.&lt;br /&gt;
&lt;br /&gt;
Institutions using GENE include research centers in Germany, USA, Switzerland, France, UK, Netherlands, Italy, Japan, India, China, South Korea, and many others.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===High-Performance Computing===&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
GENE has been at the forefront of high-performance computing in plasma physics since the 1960s. The code is designed to run efficiently on the world&#039;s largest supercomputers. In 2022, a major project was launched with €2.14 million in EU funding to develop an exascale version of GENE, pioneering the transition to exascale supercomputers.[5]&lt;br /&gt;
&lt;br /&gt;
The goal is to create &amp;quot;digital twins&amp;quot; of fusion experiments like ITER, allowing researchers to predict plasma behavior rather than just interpret experimental results.&lt;br /&gt;
&lt;br /&gt;
==Validation and Impact==&lt;br /&gt;
&lt;br /&gt;
GENE has been extensively validated against experimental measurements from major fusion devices. A landmark 2025 study demonstrated successful multi-channel validation of GENE against ASDEX Upgrade tokamak data, comparing simultaneous measurements of multiple plasma properties including turbulence amplitudes, wavenumber spectra, and cross phases.[2]&lt;br /&gt;
&lt;br /&gt;
The code has been used to:&lt;br /&gt;
* Explain turbulence suppression by fast ions in tokamak plasmas&lt;br /&gt;
* Predict similar effects in stellarators&lt;br /&gt;
* Understand energy confinement scaling&lt;br /&gt;
* Design optimal plasma scenarios for ITER&lt;br /&gt;
* Investigate the effects of different wall materials (like tungsten) on plasma performance&lt;br /&gt;
&lt;br /&gt;
==See also==&lt;br /&gt;
&lt;br /&gt;
* [[Gyrokinetics]]&lt;br /&gt;
* [[Plasma (physics)]]&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Tokamak]]&lt;br /&gt;
* [[Stellarator]]&lt;br /&gt;
* [[ITER]]&lt;br /&gt;
* [[Max Planck Institute for Plasma Physics]]&lt;br /&gt;
* [[Computational plasma physics]]&lt;br /&gt;
* [[Magnetohydrodynamics]]&lt;br /&gt;
&lt;br /&gt;
==References==&lt;br /&gt;
&lt;br /&gt;
# Jenko, F. (1999). &amp;quot;Development of GENE code&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/5295353/06_22&lt;br /&gt;
# &amp;quot;Milestone in predicting core plasma turbulence: successful multi-channel validation of the gyrokinetic code GENE&amp;quot; (2025). Nature Communications. https://www.nature.com/articles/s41467-025-56997-2&lt;br /&gt;
# Maurer, M. et al. &amp;quot;Promising computer simulations for stellarator plasmas&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/4928395/05_20&lt;br /&gt;
# &amp;quot;GENE-X: A full-f gyrokinetic turbulence code based on the flux-coordinate independent approach&amp;quot; (2021). Computer Physics Communications. https://www.sciencedirect.com/science/article/abs/pii/S0010465521000989&lt;br /&gt;
# &amp;quot;Nuclear fusion simulation to pioneer transition to exascale supercomputers&amp;quot; (2023). EUROfusion. Retrieved from https://euro-fusion.org/member-news/nuclear-fusion-simulation-to-pioneer-transition-to-exascale-supercomputers/&lt;br /&gt;
&lt;br /&gt;
==External links==&lt;br /&gt;
&lt;br /&gt;
* [https://genecode.org Official GENE website]&lt;br /&gt;
* [https://www.ipp.mpg.de Max Planck Institute for Plasma Physics]&lt;br /&gt;
* [https://github.com/genestrucutretest/GENE GENE on GitHub] (if available)&lt;br /&gt;
* [https://www.iter.org ITER Organization]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Category:Plasma physics]]&lt;br /&gt;
[[Category:Nuclear fusion]]&lt;br /&gt;
[[Category:Computational physics]]&lt;br /&gt;
[[Category:Scientific simulation software]]&lt;br /&gt;
[[Category:Physics software]]&lt;br /&gt;
[[Category:Free science software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8545</id>
		<title>GENE</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=GENE&amp;diff=8545"/>
		<updated>2026-02-09T21:46:06Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: Created page with &amp;quot;&amp;#039;&amp;#039;&amp;#039;GENE&amp;#039;&amp;#039;&amp;#039; (&amp;#039;&amp;#039;&amp;#039;Gyrokinetic Electromagnetic Numerical Experiment&amp;#039;&amp;#039;&amp;#039;) is an open-source computer simulation code used to study plasma turbulence in magnetic confinement fusion devices. GENE solves the gyrokinetic equations to simulate electromagnetic turbulence in plasmas, which is critical for understanding energy confinement in fusion reactors like tokamaks and stellarators.  ==Overview==  GENE is a gyrokinetic turbulence code that simulates plasma behavior at very small...&amp;quot;&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&#039;&#039;&#039;GENE&#039;&#039;&#039; (&#039;&#039;&#039;Gyrokinetic Electromagnetic Numerical Experiment&#039;&#039;&#039;) is an open-source computer simulation code used to study plasma turbulence in magnetic confinement fusion devices. GENE solves the gyrokinetic equations to simulate electromagnetic turbulence in plasmas, which is critical for understanding energy confinement in fusion reactors like tokamaks and stellarators.&lt;br /&gt;
&lt;br /&gt;
==Overview==&lt;br /&gt;
&lt;br /&gt;
GENE is a gyrokinetic turbulence code that simulates plasma behavior at very small scales comparable to the ion and electron gyroradius. The code was originally developed at the [[Max Planck Institute for Plasma Physics]] (IPP) in Garching, Germany, with the first version written by Frank Jenko in 1999 [1].&lt;br /&gt;
&lt;br /&gt;
GENE is widely used in the international fusion research community and is considered one of the leading codes for plasma turbulence simulations. The code has been continuously developed by an international team of researchers and is designed to run on high-performance supercomputers.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Purpose and Applications===&lt;br /&gt;
&lt;br /&gt;
The main purpose of GENE is to understand and predict turbulent transport in fusion plasmas. Plasma turbulence is one of the key factors limiting energy confinement in magnetic fusion devices, which directly affects the performance and efficiency of potential fusion power plants. By simulating this turbulence, GENE helps researchers:&lt;br /&gt;
&lt;br /&gt;
* Predict energy confinement times in fusion experiments&lt;br /&gt;
* Understand heat and particle transport mechanisms&lt;br /&gt;
* Optimize plasma conditions for better performance&lt;br /&gt;
* Design future fusion devices including ITER&lt;br /&gt;
* Validate theoretical models against experimental data&lt;br /&gt;
&lt;br /&gt;
The code has been successfully validated against experimental measurements from major fusion devices including ASDEX Upgrade and has shown excellent agreement with multiple simultaneous plasma observables.&lt;br /&gt;
&lt;br /&gt;
==Physical Model==&lt;br /&gt;
&lt;br /&gt;
GENE is based on gyrokinetic theory, which describes plasma behavior on spatial scales comparable to particle gyroradii and on time scales much slower than the cyclotron frequency. This approach reduces the complexity of the full kinetic description while retaining the essential physics of plasma turbulence.&lt;br /&gt;
&lt;br /&gt;
===Gyrokinetic Equations===&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic model assumes that:&lt;br /&gt;
* The plasma is strongly magnetized&lt;br /&gt;
* Perpendicular spatial scales are comparable to the ion gyroradius&lt;br /&gt;
* Frequencies are much lower than the ion cyclotron frequency&lt;br /&gt;
* Perturbations are small compared to background quantities&lt;br /&gt;
&lt;br /&gt;
The fundamental equations solved by GENE include:&lt;br /&gt;
&lt;br /&gt;
====Gyrokinetic Vlasov Equation====&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic equation describes the evolution of the perturbed distribution function. In simplified form, it can be written as:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\frac{\partial h_s}{\partial t} + \mathbf{v}_{\text{gc}} \cdot \nabla h_s + \dot{v}_\parallel \frac{\partial h_s}{\partial v_\parallel} = C(h_s)&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
where:&lt;br /&gt;
* &amp;lt;math&amp;gt;h_s&amp;lt;/math&amp;gt; is the perturbed distribution function for species &#039;&#039;s&#039;&#039;&lt;br /&gt;
* &amp;lt;math&amp;gt;\mathbf{v}_{\text{gc}}&amp;lt;/math&amp;gt; is the guiding center velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;v_\parallel&amp;lt;/math&amp;gt; is the parallel velocity&lt;br /&gt;
* &amp;lt;math&amp;gt;C(h_s)&amp;lt;/math&amp;gt; represents collisional effects&lt;br /&gt;
&lt;br /&gt;
====Maxwell&#039;s Equations====&lt;br /&gt;
&lt;br /&gt;
GENE couples the gyrokinetic equation to Maxwell&#039;s equations to determine the electromagnetic fields. In the electrostatic approximation, this reduces to the quasineutrality condition:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;\sum_s Z_s e B \int dv_\parallel \, d\mu \, d\varphi \, h_s(\mathbf{R}) = \sum_s \frac{Z_s^2 e^2 n_s \phi}{T_s}&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
For electromagnetic simulations, GENE also solves Ampère&#039;s law for the parallel magnetic field perturbations.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===Turbulence Mechanisms===&lt;br /&gt;
&lt;br /&gt;
GENE can simulate various types of plasma turbulence, including:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Ion Temperature Gradient (ITG) modes&#039;&#039;&#039; - driven by temperature gradients in the plasma&lt;br /&gt;
* &#039;&#039;&#039;Trapped Electron Modes (TEM)&#039;&#039;&#039; - caused by particles trapped in magnetic field variations&lt;br /&gt;
* &#039;&#039;&#039;Electron Temperature Gradient (ETG) modes&#039;&#039;&#039; - electron-scale turbulence&lt;br /&gt;
* &#039;&#039;&#039;Kinetic Ballooning Modes (KBM)&#039;&#039;&#039; - pressure-driven instabilities&lt;br /&gt;
* &#039;&#039;&#039;Microtearing modes&#039;&#039;&#039; - electromagnetic instabilities that can tear magnetic field lines&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Numerical Methods==&lt;br /&gt;
&lt;br /&gt;
GENE is a Eulerian code, meaning it solves the gyrokinetic equations on a fixed grid in phase space rather than following individual particles. This approach has several advantages for turbulence simulations.&lt;br /&gt;
&lt;br /&gt;
===Discretization===&lt;br /&gt;
&lt;br /&gt;
The code uses a combination of numerical methods:&lt;br /&gt;
* &#039;&#039;&#039;Spectral methods&#039;&#039;&#039; in the perpendicular directions (for periodic boundary conditions)&lt;br /&gt;
* &#039;&#039;&#039;Finite differences&#039;&#039;&#039; in the radial direction (for global simulations)&lt;br /&gt;
* &#039;&#039;&#039;Upwind schemes&#039;&#039;&#039; along magnetic field lines&lt;br /&gt;
* &#039;&#039;&#039;Runge-Kutta methods&#039;&#039;&#039; for time integration&lt;br /&gt;
&lt;br /&gt;
===Coordinate Systems===&lt;br /&gt;
&lt;br /&gt;
GENE employs field-aligned coordinates that follow magnetic field lines, which is natural for strongly magnetized plasmas. Different versions of the code use different coordinate approaches:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Standard GENE&#039;&#039;&#039; - uses flux-tube or radially global geometry in tokamaks&lt;br /&gt;
* &#039;&#039;&#039;GENE-3D&#039;&#039;&#039; - full three-dimensional geometry for stellarators&lt;br /&gt;
* &#039;&#039;&#039;GENE-X&#039;&#039;&#039; - flux-coordinate independent (FCI) approach for edge and scrape-off layer regions&lt;br /&gt;
&lt;br /&gt;
==Code Versions and Extensions==&lt;br /&gt;
&lt;br /&gt;
===Local and Global Versions===&lt;br /&gt;
&lt;br /&gt;
GENE can operate in different spatial modes:&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;Local (flux-tube)&#039;&#039;&#039; - simulates a small radial region with periodic boundary conditions; computationally efficient for core turbulence&lt;br /&gt;
* &#039;&#039;&#039;Radially global&#039;&#039;&#039; - includes variations across the plasma radius; necessary for edge effects and profile evolution&lt;br /&gt;
&lt;br /&gt;
===GENE-3D===&lt;br /&gt;
&lt;br /&gt;
GENE-3D is an extension that handles the complex three-dimensional geometry of stellarators. Development of GENE-3D took approximately five years and was presented by Maurice Maurer and colleagues.[3] Unlike the original tokamak-oriented version, GENE-3D can simulate the full ion and electron dynamics in the complex magnetic field geometry of stellarators like Wendelstein 7-X.&lt;br /&gt;
&lt;br /&gt;
===GENE-X===&lt;br /&gt;
&lt;br /&gt;
GENE-X is a full-f gyrokinetic continuum code based on the flux-coordinate independent (FCI) approach.[4] This version was developed specifically to handle:&lt;br /&gt;
&lt;br /&gt;
* Edge and scrape-off layer turbulence&lt;br /&gt;
* Regions with magnetic X-points (where traditional field-aligned coordinates have singularities)&lt;br /&gt;
* Geometries without well-defined flux surfaces&lt;br /&gt;
* Transition regions between core and edge plasma&lt;br /&gt;
&lt;br /&gt;
GENE-X uses unstructured, locally Cartesian grids that provide flexibility while maintaining computational efficiency. The code is capable of simulating regions from the magnetic axis, across the separatrix, and into the scrape-off layer.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Development and Community==&lt;br /&gt;
&lt;br /&gt;
===History===&lt;br /&gt;
&lt;br /&gt;
Frank Jenko wrote the first version of GENE in 1999 during his early postdoctoral work.[1] Since then, the code has been continuously developed and improved by an international team of researchers. Major development centers include:&lt;br /&gt;
&lt;br /&gt;
* Max Planck Institute for Plasma Physics (IPP), Garching, Germany&lt;br /&gt;
* Max Planck Computing and Data Facility (MPCDF), Germany&lt;br /&gt;
* Technical University of Munich, Germany&lt;br /&gt;
* University of Texas at Austin, USA&lt;br /&gt;
* École Polytechnique Fédérale de Lausanne (EPFL), Switzerland&lt;br /&gt;
* Many other international institutions&lt;br /&gt;
&lt;br /&gt;
===International Collaboration===&lt;br /&gt;
&lt;br /&gt;
The GENE Development Team is an international collaboration that includes members from universities and research laboratories across the world. The project welcomes contributions from the global fusion community and maintains an open-source development model.&lt;br /&gt;
&lt;br /&gt;
Institutions using GENE include research centers in Germany, USA, Switzerland, France, UK, Netherlands, Italy, Japan, India, China, South Korea, and many others.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===High-Performance Computing===&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
GENE has been at the forefront of high-performance computing in plasma physics since the 1960s. The code is designed to run efficiently on the world&#039;s largest supercomputers. In 2022, a major project was launched with €2.14 million in EU funding to develop an exascale version of GENE, pioneering the transition to exascale supercomputers.[5]&lt;br /&gt;
&lt;br /&gt;
The goal is to create &amp;quot;digital twins&amp;quot; of fusion experiments like ITER, allowing researchers to predict plasma behavior rather than just interpret experimental results.&lt;br /&gt;
&lt;br /&gt;
==Validation and Impact==&lt;br /&gt;
&lt;br /&gt;
GENE has been extensively validated against experimental measurements from major fusion devices. A landmark 2025 study demonstrated successful multi-channel validation of GENE against ASDEX Upgrade tokamak data, comparing simultaneous measurements of multiple plasma properties including turbulence amplitudes, wavenumber spectra, and cross phases.[2]&lt;br /&gt;
&lt;br /&gt;
The code has been used to:&lt;br /&gt;
* Explain turbulence suppression by fast ions in tokamak plasmas&lt;br /&gt;
* Predict similar effects in stellarators&lt;br /&gt;
* Understand energy confinement scaling&lt;br /&gt;
* Design optimal plasma scenarios for ITER&lt;br /&gt;
* Investigate the effects of different wall materials (like tungsten) on plasma performance&lt;br /&gt;
&lt;br /&gt;
==See also==&lt;br /&gt;
&lt;br /&gt;
* [[Gyrokinetics]]&lt;br /&gt;
* [[Plasma (physics)]]&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[Tokamak]]&lt;br /&gt;
* [[Stellarator]]&lt;br /&gt;
* [[ITER]]&lt;br /&gt;
* [[Max Planck Institute for Plasma Physics]]&lt;br /&gt;
* [[Computational plasma physics]]&lt;br /&gt;
* [[Magnetohydrodynamics]]&lt;br /&gt;
&lt;br /&gt;
==References==&lt;br /&gt;
&lt;br /&gt;
# Jenko, F. (1999). &amp;quot;Development of GENE code&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/5295353/06_22&lt;br /&gt;
# &amp;quot;Milestone in predicting core plasma turbulence: successful multi-channel validation of the gyrokinetic code GENE&amp;quot; (2025). Nature Communications. https://www.nature.com/articles/s41467-025-56997-2&lt;br /&gt;
# Maurer, M. et al. &amp;quot;Promising computer simulations for stellarator plasmas&amp;quot;. Max Planck Institute for Plasma Physics. Retrieved from https://www.ipp.mpg.de/4928395/05_20&lt;br /&gt;
# &amp;quot;GENE-X: A full-f gyrokinetic turbulence code based on the flux-coordinate independent approach&amp;quot; (2021). Computer Physics Communications. https://www.sciencedirect.com/science/article/abs/pii/S0010465521000989&lt;br /&gt;
# &amp;quot;Nuclear fusion simulation to pioneer transition to exascale supercomputers&amp;quot; (2023). EUROfusion. Retrieved from https://euro-fusion.org/member-news/nuclear-fusion-simulation-to-pioneer-transition-to-exascale-supercomputers/&lt;br /&gt;
&lt;br /&gt;
==External links==&lt;br /&gt;
&lt;br /&gt;
* [https://genecode.org Official GENE website]&lt;br /&gt;
* [https://www.ipp.mpg.de Max Planck Institute for Plasma Physics]&lt;br /&gt;
* [https://github.com/genestrucutretest/GENE GENE on GitHub] (if available)&lt;br /&gt;
* [https://www.iter.org ITER Organization]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Category:Plasma physics]]&lt;br /&gt;
[[Category:Nuclear fusion]]&lt;br /&gt;
[[Category:Computational physics]]&lt;br /&gt;
[[Category:Scientific simulation software]]&lt;br /&gt;
[[Category:Physics software]]&lt;br /&gt;
[[Category:Free science software]]&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Plasma_simulation&amp;diff=8544</id>
		<title>Plasma simulation</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Plasma_simulation&amp;diff=8544"/>
		<updated>2026-02-09T20:20:38Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;The complexity of fusion-grade plasmas and the increased computational power that has become available in recent years has made the simulation of plasmas a prime object of study in the field of fusion research. Although the basic equations governing the behaviour of magnetised plasmas are known, approximations are always necessary in any code of practical interest; e.g. the extreme disparity of the transport timescales (seconds) and turbulent timescales (microseconds) make it hard to perform detailed turbulence simulations for the whole three-dimensional plasma volume and for several transport timescales.&lt;br /&gt;
&lt;br /&gt;
This page discusses plasma transport calculations, not the [[MHD equilibrium]]. &lt;br /&gt;
&lt;br /&gt;
== Projects ==&lt;br /&gt;
&lt;br /&gt;
* [http://www.lehigh.edu/~infusion/ Fusion Simulation Project] (USA) &lt;br /&gt;
&lt;br /&gt;
== Codes ==&lt;br /&gt;
&lt;br /&gt;
Codes can either be interpretative (taking some input from experiment) or predictive.&lt;br /&gt;
They can be full-[[Tokamak|tokamak]] (or full-[[Stellarator|stellarator]]), or simulate only a small portion of plasma (a [[Flux tube|flux tube]], the edge, or the [[Scrape-Off Layer]]). They can be fluid models for one (electrons), two (electrons + ions) or more ([[impurities]]) fluid species, Monte Carlo type (particle tracing) codes, or gyro-kinetic codes. The latter are again subdivided into full-f or delta-f codes (delta-f referring to the fact that only the deviation from a background Maxwellian particle velocity distribution function is simulated).&lt;br /&gt;
&lt;br /&gt;
Recent years have seen an increased effort in the field of cross code benchmarking.&lt;br /&gt;
&amp;lt;ref&amp;gt;Nevins W.M. et al, [[doi:10.1063/1.2402510|Phys. Plasmas &#039;&#039;&#039;13&#039;&#039;&#039; (2006) 122306]]&amp;lt;/ref&amp;gt;&lt;br /&gt;
&amp;lt;ref&amp;gt;A.M. Dimits et al, [[doi:10.1088/0029-5515/47/8/012|Nucl. Fusion &#039;&#039;&#039;47&#039;&#039;&#039; (2007) 817-824]]&amp;lt;/ref&amp;gt;&lt;br /&gt;
&amp;lt;ref&amp;gt;G L Falchetto et al, [[doi:10.1088/0741-3335/50/12/124015|Plasma Phys. Control. Fusion &#039;&#039;&#039;50&#039;&#039;&#039; (2008) 124015]]&amp;lt;/ref&amp;gt;&lt;br /&gt;
&amp;lt;ref&amp;gt;[http://w3.pppl.gov/ntcc/ National Transport Code Collaboration]&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
=== Fluid codes ===&lt;br /&gt;
&lt;br /&gt;
In the fluid model approach, equations are derived for the moments of the distribution function f. This approach requires making several more or less strong assumptions regarding the relative importance of physical phenomena and closing the infinite set of moment equations, thus possibly losing some interesting physics.&lt;br /&gt;
&lt;br /&gt;
* [[CUTIE]] (predictive, 3-D, full-tokamak)&lt;br /&gt;
* [[PRETOR]]&lt;br /&gt;
* [[PROCTR]] (1-D)&lt;br /&gt;
* [[TRANSP]]&lt;br /&gt;
* [[JETTO]]&lt;br /&gt;
* [[MMM95]]&lt;br /&gt;
* [[EDGE2D-NIMBUS]] (edge)&lt;br /&gt;
* [[UEDGE]]&lt;br /&gt;
* [[SOLPS]]&lt;br /&gt;
* [[EMC3-EIRENE]]&amp;lt;ref&amp;gt;[[doi:10.1002/ctpp.201410092|Y. Feng et al, Contrib. Plasma Phys. &#039;&#039;&#039;54&#039;&#039;&#039; (2014) 426-431]]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* [[FINDIF]] &amp;lt;ref&amp;gt;https://hsx.wisc.edu/wp-content/uploads/sites/747/2022/10/Findif_nvTT_3.19-G.Pelka_.pdf&amp;lt;/ref&amp;gt;&lt;br /&gt;
* [[BOUT++]]&amp;lt;ref&amp;gt;https://boutproject.github.io&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
=== Monte Carlo codes ===&lt;br /&gt;
&lt;br /&gt;
The Monte Carlo or single particle approach solves the kinetic single-particle equations (the Lorentz force equation) in a fixed background.&lt;br /&gt;
&lt;br /&gt;
* [[MOCA]]&lt;br /&gt;
* [[EIRENE]] (edge)&lt;br /&gt;
&lt;br /&gt;
=== Gyrokinetic codes ===&lt;br /&gt;
&lt;br /&gt;
The gyrokinetic treatment simplifies the [[:Wikipedia:Vlasov_equation|Vlasov equation]] for the evolution of the single-particle distribution function &amp;lt;math&amp;gt;f(\vec{x},\vec{v},t)&amp;lt;/math&amp;gt; by averaging over the gyration angle, resulting in an evolution equation for the particle guiding centre.&lt;br /&gt;
See [[Gyrokinetic simulations]].&lt;br /&gt;
&lt;br /&gt;
* [[GYRO]] &amp;lt;ref&amp;gt;[http://fusion.gat.com/theory/Gyro Gyro homepage]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* [[GS2]] ([[Flux tube|flux tube]])&lt;br /&gt;
* [[GENE]] ([[Flux tube|flux tube]])&lt;br /&gt;
* [[GEM]] (delta f) &amp;lt;ref&amp;gt;[http://cips.colorado.edu/simulation/gem.htm Plasma Simulation Group]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* [[EUTERPE]]&lt;br /&gt;
* [[SUMMIT/PG3EQ_NC]]&lt;br /&gt;
&lt;br /&gt;
== Validation ==&lt;br /&gt;
&lt;br /&gt;
See [[Model validation]]&lt;br /&gt;
&lt;br /&gt;
== See Also ==&lt;br /&gt;
* [[Neutronics in Fusion]]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references /&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Breeding_blanket&amp;diff=8543</id>
		<title>Breeding blanket</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Breeding_blanket&amp;diff=8543"/>
		<updated>2026-02-09T19:04:32Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* See also */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[[File:ITER_Blanket_modules.png|400px|thumb|right|ITER Blanket Modules, acting as a shield for the heat load inside the vacuum chamber and for the high-energy neutrons produced in the fusion reactions.]]&lt;br /&gt;
&lt;br /&gt;
The breeding blanket consists of a set of modules covering the interior of the fusion reactor vessel, capable of supporting a high heat load and an intense neutron flux. Its main purpose is threefold:&lt;br /&gt;
# to assure self-sufficiency of the fusion reactor with regard to tritium (by producing, from lithium, at least the same amount of tritium as that which is consumed in the plasma), &lt;br /&gt;
# to maximise the net efficiency of the power plant (by assuring the highest possible temperature of the coolant), and&lt;br /&gt;
# to act as a radiation barrier (such that the components behind the breeding blanket receive the lowest amount of radiation possible). &lt;br /&gt;
&lt;br /&gt;
Currently, Europe is developing two alternative concepts for the breeding blanket of [[DEMO]], both based on helium cooling, which must be tested in experiments to be performed at [[ITER]]. One is based on liquid metal, and the other on the use of Li and Be ceramics (acting as neutron multipliers) in the shape of small spheres.&lt;br /&gt;
&amp;lt;ref&amp;gt;[http://dx.doi.org/10.1016/j.fusengdes.2005.09.005 R. Andreani et al., Fusion Engineering and Design &#039;&#039;&#039;81&#039;&#039;&#039;, Issues 1-7 (2006) 25-32 ]&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== See also ==&lt;br /&gt;
* The [[TECNO FUS]] project&lt;br /&gt;
* The Goal Oriented Training [[EUROBREED]]&lt;br /&gt;
* The [[Neutronics in Fusion]] page.&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references /&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8542</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8542"/>
		<updated>2026-02-09T19:00:49Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8541</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8541"/>
		<updated>2026-02-09T19:00:08Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8540</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8540"/>
		<updated>2026-02-09T18:59:21Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* References */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Counters&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8539</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8539"/>
		<updated>2026-02-09T18:56:14Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* References */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Counters&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ https://www.sciencedirect.com/science/article/abs/pii/S030645491400379X?via%3Dihub&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Counters&amp;quot;&amp;gt;Springer, “Neutron Diagnostics for Tokamak Plasma”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8538</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8538"/>
		<updated>2026-02-09T18:54:12Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* References */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Counters&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &amp;quot;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&amp;quot;, *Annals of Nuclear Energy*, (published articles on Serpent include: https://www.sciencedirect.com/science/article/abs/pii/S0306454914004095)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ :contentReference[oaicite:3]{index=3}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Counters&amp;quot;&amp;gt;Springer, “Neutron Diagnostics for Tokamak Plasma”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8537</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8537"/>
		<updated>2026-02-09T18:52:09Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* References */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Counters&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://iopscience.iop.org/article/10.1088/1741-4326/ac3be4&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., *The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics*, *Annals of Nuclear Energy*, (published articles on Serpent include: https://doi.org/10.1016/j.anucene.2014.07.018)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ :contentReference[oaicite:3]{index=3}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Counters&amp;quot;&amp;gt;Springer, “Neutron Diagnostics for Tokamak Plasma”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8536</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8536"/>
		<updated>2026-02-09T18:51:10Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* References */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Counters&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://iopscience.iop.org/article/10.1088/1361-6587/aba8d7&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://doi.org/10.1088/1741-4326/ac1d3f&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., *The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics*, *Annals of Nuclear Energy*, (published articles on Serpent include: https://doi.org/10.1016/j.anucene.2014.07.018)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ :contentReference[oaicite:3]{index=3}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Counters&amp;quot;&amp;gt;Springer, “Neutron Diagnostics for Tokamak Plasma”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8535</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8535"/>
		<updated>2026-02-09T18:49:35Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* References */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Counters&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://doi.org/10.1088/1361-6587/abca7d&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://doi.org/10.1088/1741-4326/ac1d3f&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., *The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics*, *Annals of Nuclear Energy*, (published articles on Serpent include: https://doi.org/10.1016/j.anucene.2014.07.018)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ :contentReference[oaicite:3]{index=3}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Counters&amp;quot;&amp;gt;Springer, “Neutron Diagnostics for Tokamak Plasma”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8534</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8534"/>
		<updated>2026-02-09T18:48:53Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* References */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Counters&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, vol. 62, 2020. https://doi.org/10.1088/1361-6587/aba8d7 :contentReference[oaicite:3]{index=3}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://doi.org/10.1088/1741-4326/ac1d3f&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., *The Serpent Monte Carlo code: status, development and applications in fusion neutronics*, *Annals of Nuclear Energy*, vol. 82, 2015. https://doi.org/10.1016/j.anucene.2014.08.024 :contentReference[oaicite:4]{index=4}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A state-of-the-art Monte Carlo code for research and development,” *Annals of Nuclear Energy*, vol. 82, 2015. https://doi.org/10.1016/j.anucene.2014.07.048 :contentReference[oaicite:5]{index=5}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (e.g., official PHITS details at https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Counters&amp;quot;&amp;gt;Springer, “Neutron Diagnostics for Tokamak Plasma”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8533</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8533"/>
		<updated>2026-02-09T18:43:49Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* References */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Counters&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021. https://doi.org/10.1088/1361-6587/abca7d :contentReference[oaicite:0]{index=0}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018. https://doi.org/10.1016/j.fusengdes.2018.04.065&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, no. 3, 2004. https://doi.org/10.1016/j.cpc.2003.11.002 :contentReference[oaicite:1]{index=1}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020. https://doi.org/10.1088/1361-6587/abca7d&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022. https://doi.org/10.1088/1741-4326/ac1d3f&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7-X: effect of magnetic configuration,” arXiv:2009.02925, 2020. https://arxiv.org/abs/2009.02925&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), *MCNP User’s Manual – Code Version 6.2*, Los Alamos National Laboratory, LA-UR-17-29981. https://mcnpx.lanl.gov/ :contentReference[oaicite:2]{index=2}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., *The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics*, *Annals of Nuclear Energy*, (published articles on Serpent include: https://doi.org/10.1016/j.anucene.2014.07.018)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., “OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development,” *Annals of Nuclear Energy* (recommended citation) and official OpenMC docs at https://docs.openmc.org/ :contentReference[oaicite:3]{index=3}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., “Features of Particle and Heavy Ion Transport Code System (PHITS),” *Journal of Nuclear Science and Technology*. (See official PHITS site for journal articles: https://phits.jaea.go.jp/)&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Counters&amp;quot;&amp;gt;Springer, “Neutron Diagnostics for Tokamak Plasma”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. https://link.springer.com/article/10.1007/s10894-018-0183-0&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. https://arxiv.org/abs/1902.07633&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Springer, “Neutron Diagnostics in Tokamaks”, 2018. https://link.springer.com/article/10.1007/s10894-018-0195-9&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8532</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8532"/>
		<updated>2026-02-09T18:42:06Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* External links */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Counters&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – ITER]&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, 2004.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast‑ion D‑alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET‑C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7‑X: effect of magnetic configuration,” arXiv:2009.02925, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), &#039;&#039;MCNP User’s Manual – Code Version 6.2&#039;&#039;, Los Alamos National Laboratory, LA-UR-17-29981.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &#039;&#039;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., &#039;&#039;OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., &#039;&#039;Features of Particle and Heavy Ion Transport Code System (PHITS)&#039;&#039;, Journal of Nuclear Science and Technology.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Counters&amp;quot;&amp;gt;Link to neutron counters / flux monitor review: Springer, “Neutron Diagnostics for Tokamak Plasma”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0195-9]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Activation detectors review: Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0183-0]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;Spectrometer review: ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. [https://arxiv.org/abs/1902.07633]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Diamond and SiC detectors: Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. [https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;Scintillator detectors: ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. [https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Neutron cameras and spatial diagnostics: Springer, “Neutron Diagnostics in Tokamaks”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0195-9]&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8531</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8531"/>
		<updated>2026-02-09T18:41:25Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* External links */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Counters&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
* [https://www.iter.org/machine/supporting-systems/tritium-breeding Tritium Breeding – Wikipedia article]&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, 2004.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast‑ion D‑alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET‑C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7‑X: effect of magnetic configuration,” arXiv:2009.02925, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), &#039;&#039;MCNP User’s Manual – Code Version 6.2&#039;&#039;, Los Alamos National Laboratory, LA-UR-17-29981.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &#039;&#039;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., &#039;&#039;OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., &#039;&#039;Features of Particle and Heavy Ion Transport Code System (PHITS)&#039;&#039;, Journal of Nuclear Science and Technology.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Counters&amp;quot;&amp;gt;Link to neutron counters / flux monitor review: Springer, “Neutron Diagnostics for Tokamak Plasma”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0195-9]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Activation detectors review: Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0183-0]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;Spectrometer review: ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. [https://arxiv.org/abs/1902.07633]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Diamond and SiC detectors: Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. [https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;Scintillator detectors: ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. [https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Neutron cameras and spatial diagnostics: Springer, “Neutron Diagnostics in Tokamaks”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0195-9]&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8523</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8523"/>
		<updated>2026-02-04T23:21:23Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
The progress in neutron detectors for fusion devices has enabled increasingly precise measurements of neutron flux, energy spectra, and spatial emission profiles. Advances in detector technology and modeling now allow researchers to better assess key plasma parameters, including fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Counters&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= External links =&lt;br /&gt;
* [https://link.springer.com/book/10.1007/978-981-10-5469-3 Neutronics in Fusion Reactors – Springer Book]&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Nuclear_fusion Nuclear Fusion – Wikipedia article]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, 2004.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast‑ion D‑alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET‑C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7‑X: effect of magnetic configuration,” arXiv:2009.02925, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), &#039;&#039;MCNP User’s Manual – Code Version 6.2&#039;&#039;, Los Alamos National Laboratory, LA-UR-17-29981.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &#039;&#039;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., &#039;&#039;OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., &#039;&#039;Features of Particle and Heavy Ion Transport Code System (PHITS)&#039;&#039;, Journal of Nuclear Science and Technology.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Counters&amp;quot;&amp;gt;Link to neutron counters / flux monitor review: Springer, “Neutron Diagnostics for Tokamak Plasma”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0195-9]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Activation detectors review: Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0183-0]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;Spectrometer review: ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. [https://arxiv.org/abs/1902.07633]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Diamond and SiC detectors: Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. [https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;Scintillator detectors: ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. [https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Neutron cameras and spatial diagnostics: Springer, “Neutron Diagnostics in Tokamaks”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0195-9]&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8522</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8522"/>
		<updated>2026-02-04T23:09:41Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* Useful GitHub Repositories for Neutronics in Nuclear Fusion */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
Neutron detectors are essential diagnostic tools in fusion devices, used to measure neutron flux, energy spectra, and spatial emission profiles. They help assess plasma parameters such as fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Counters&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, 2004.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast‑ion D‑alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET‑C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7‑X: effect of magnetic configuration,” arXiv:2009.02925, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), &#039;&#039;MCNP User’s Manual – Code Version 6.2&#039;&#039;, Los Alamos National Laboratory, LA-UR-17-29981.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &#039;&#039;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., &#039;&#039;OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., &#039;&#039;Features of Particle and Heavy Ion Transport Code System (PHITS)&#039;&#039;, Journal of Nuclear Science and Technology.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Counters&amp;quot;&amp;gt;Link to neutron counters / flux monitor review: Springer, “Neutron Diagnostics for Tokamak Plasma”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0195-9]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Activation detectors review: Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0183-0]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;Spectrometer review: ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. [https://arxiv.org/abs/1902.07633]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Diamond and SiC detectors: Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. [https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;Scintillator detectors: ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. [https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Neutron cameras and spatial diagnostics: Springer, “Neutron Diagnostics in Tokamaks”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0195-9]&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8521</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8521"/>
		<updated>2026-02-04T23:08:12Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Neutron Detectors in Fusion Tokamaks =&lt;br /&gt;
&lt;br /&gt;
Neutron detectors are essential diagnostic tools in fusion devices, used to measure neutron flux, energy spectra, and spatial emission profiles. They help assess plasma parameters such as fusion power, ion temperature, and fuel composition.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable sortable&amp;quot;&lt;br /&gt;
! Method&lt;br /&gt;
! Principle&lt;br /&gt;
! Measures&lt;br /&gt;
! Typical Technology&lt;br /&gt;
! Pros&lt;br /&gt;
! Cons&lt;br /&gt;
! Use in Tokamaks&lt;br /&gt;
! Numerical Tools&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Counters and Flux Monitors&amp;lt;ref name=&amp;quot;Counters&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charged particle reactions in gas or fissile material&lt;br /&gt;
| Neutron flux / total yield&lt;br /&gt;
| ³He, BF₃ counters, U-235 / U-238 fission chambers, ionization chambers&lt;br /&gt;
| Robust, wide dynamic range, gamma discrimination&lt;br /&gt;
| Limited energy information, saturation at very high flux&lt;br /&gt;
| Real-time flux monitoring, fusion power measurement&lt;br /&gt;
| MCNP, FLUKA&lt;br /&gt;
|-&lt;br /&gt;
| Activation Detectors&amp;lt;ref name=&amp;quot;Activation&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce activation in target material&lt;br /&gt;
| Time-integrated neutron fluence&lt;br /&gt;
| Metal foils (Au, In, Al, Nb), delayed neutron activation&lt;br /&gt;
| Simple, high flux tolerant, immune to EM noise&lt;br /&gt;
| Not real-time, requires post-shot analysis&lt;br /&gt;
| Absolute neutron yield calibration, benchmarking&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Spectrometers (Recoil-Based)&amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce recoil of charged particles&lt;br /&gt;
| Neutron energy spectrum&lt;br /&gt;
| Magnetic Proton Recoil (MPR), proton recoil telescopes, silicon detectors&lt;br /&gt;
| High energy resolution, provides ion temperature and fuel ratio&lt;br /&gt;
| Bulky, sensitive to background, complex shielding&lt;br /&gt;
| Plasma ion temperature, fuel ratio, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Solid-State Neutron Detectors&amp;lt;ref name=&amp;quot;SolidState&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce charge in solid-state detector&lt;br /&gt;
| Flux and partial spectral information&lt;br /&gt;
| CVD diamond, SiC detectors&lt;br /&gt;
| Compact, fast response, radiation hard&lt;br /&gt;
| Limited efficiency, calibration complexity&lt;br /&gt;
| ITER-relevant diagnostics, high-flux measurements&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Scintillator-Based Neutron Detectors&amp;lt;ref name=&amp;quot;Scintillators&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce light pulses in scintillator&lt;br /&gt;
| Flux, timing, limited spectral information&lt;br /&gt;
| Liquid or plastic scintillators + PMT/SiPM&lt;br /&gt;
| Fast, allows neutron/gamma discrimination&lt;br /&gt;
| Radiation damage, sensitive to magnetic fields&lt;br /&gt;
| Time-resolved neutron flux, pulse shape discrimination&lt;br /&gt;
| GEANT4&lt;br /&gt;
|-&lt;br /&gt;
| Neutron Cameras&amp;lt;ref name=&amp;quot;Cameras&amp;quot;/&amp;gt;&lt;br /&gt;
| Neutrons induce signals in collimated detectors&lt;br /&gt;
| Spatial neutron emissivity (line-integrated)&lt;br /&gt;
| Scintillator or diamond arrays with collimation&lt;br /&gt;
| Spatially resolved plasma information&lt;br /&gt;
| Heavy shielding, complex neutronics&lt;br /&gt;
| Plasma profile mapping, fast-ion studies&lt;br /&gt;
| MCNP, GEANT4&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Useful GitHub Repositories for Neutronics in Nuclear Fusion =&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – Provides Python tools to generate parametric tokamak neutron sources for Monte Carlo transport codes such as OpenMC and MCNP, based on plasma profiles and fusion reaction distributions. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – A Python package to create an arbitrary parametric tokamak neutron source for use with Monte Carlo radiation transport codes such as OpenMC and MCNP. It allows specification of plasma profiles (ion density, temperature, equilibrium) and exports source definitions for neutronics simulations. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= See Also =&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
= References =&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, 2004.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast‑ion D‑alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET‑C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7‑X: effect of magnetic configuration,” arXiv:2009.02925, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), &#039;&#039;MCNP User’s Manual – Code Version 6.2&#039;&#039;, Los Alamos National Laboratory, LA-UR-17-29981.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &#039;&#039;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., &#039;&#039;OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., &#039;&#039;Features of Particle and Heavy Ion Transport Code System (PHITS)&#039;&#039;, Journal of Nuclear Science and Technology.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Counters&amp;quot;&amp;gt;Link to neutron counters / flux monitor review: Springer, “Neutron Diagnostics for Tokamak Plasma”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0195-9]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Activation&amp;quot;&amp;gt;Activation detectors review: Springer, “Neutron Activation Techniques in Fusion Devices”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0183-0]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Spectrometers&amp;quot;&amp;gt;Spectrometer review: ArXiv, “Proton Recoil Neutron Spectrometers for Tokamak Diagnostics”, 2019. [https://arxiv.org/abs/1902.07633]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;SolidState&amp;quot;&amp;gt;Diamond and SiC detectors: Eurofusion, “Diagnostic of Fusion Neutrons on JET Using Diamond Detector”, 2017. [https://scipub.euro-fusion.org/archives/jet-archive/diagnostic-of-fusion-neutrons-on-jet-tokamak-using-diamond-detector/]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Scintillators&amp;quot;&amp;gt;Scintillator detectors: ScienceDirect, “Design of Compact Neutron Detector for Tokamak”, 2025. [https://www.sciencedirect.com/science/article/abs/pii/S0168900225002578]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* &amp;lt;ref name=&amp;quot;Cameras&amp;quot;&amp;gt;Neutron cameras and spatial diagnostics: Springer, “Neutron Diagnostics in Tokamaks”, 2018. [https://link.springer.com/article/10.1007/s10894-018-0195-9]&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Nuclear_fusion&amp;diff=8520</id>
		<title>Nuclear fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Nuclear_fusion&amp;diff=8520"/>
		<updated>2026-02-04T22:11:43Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* See also */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Nuclear fusion is the process by which multiple like-charged atomic nuclei join together to form a heavier nucleus. It is accompanied by the release or absorption of energy.&lt;br /&gt;
See [[:Wikipedia:Nuclear_fusion|Wikipedia: Nuclear fusion]].&lt;br /&gt;
&lt;br /&gt;
== Energy policy issues ==&lt;br /&gt;
&lt;br /&gt;
There exist a wide consensus that the current methods for energy production are unsatisfactory in the long term, due to contamination, the greenhouse effect, diminishing resources, etc.&lt;br /&gt;
In order to decide what energy generation methods should be used, the pros and contras of each method should be considered carefully.&lt;br /&gt;
&amp;lt;ref&amp;gt;[http://en.wikipedia.org/wiki/Energy_development Energy development]&amp;lt;/ref&amp;gt;&lt;br /&gt;
Thus, making a policy choice in favour of one or the other energy option requires defining one&#039;s stance on:&lt;br /&gt;
* The importance of climate change and the impact of the burning of fossil fuels&amp;lt;ref&amp;gt;[http://en.wikipedia.org/wiki/Intergovernmental_Panel_on_Climate_Change Intergovernmental Panel on Climate Change]&amp;lt;/ref&amp;gt;&amp;lt;ref&amp;gt;[http://www.newscientist.com/article/dn11462 Climate change: A guide for the perplexed]&amp;lt;/ref&amp;gt;&amp;lt;ref&amp;gt;[http://www.youtube.com/watch?v=2T4UF_Rmlio The American denial of Global Warming]&amp;lt;/ref&amp;gt;&lt;br /&gt;
* Quantitative estimates of the energy generation potential of each of the available energy options&lt;br /&gt;
* Estimates of global population growth&amp;lt;ref&amp;gt;[http://en.wikipedia.org/wiki/Population_growth Population growth]&amp;lt;/ref&amp;gt;&amp;lt;ref&amp;gt;[http://www.populationconnection.org/ PopulationConnection.org]&amp;lt;/ref&amp;gt; and expectations regarding future energy demand&amp;lt;ref&amp;gt;[http://www.worldenergyoutlook.org/ World Energy Outlook]&amp;lt;/ref&amp;gt;&amp;lt;ref&amp;gt;[http://www.eia.doe.gov/ U.S. Energy Information Administration]&amp;lt;/ref&amp;gt;, taking into account the rapidly rising energy needs of emerging economies&lt;br /&gt;
* The relative importance of the environmental impact of each of the energy options&lt;br /&gt;
* Social threats associated with each energy option: e.g., nuclear proliferation, or the threats associated with politically unstable energy supply regions&lt;br /&gt;
* The social acceptability of each energy option&lt;br /&gt;
* The relative economic cost of each of the energy options (contemplating the complete energy generation trajectory, including environmental damage and clean-up)&lt;br /&gt;
* Opportunities offered by the energy options in terms of, e.g., economic stimulation and employment&lt;br /&gt;
Making the correct choice requires studying each of these complex issues and somehow balancing the risks and opportunities involved.&lt;br /&gt;
For some of them, the future evolution can be predicted with some confidence, &lt;br /&gt;
but for others the predictions are hotly debated.&lt;br /&gt;
&lt;br /&gt;
In any case, the choice for any specific energy generation options should not be considered in isolation from other global issues, such as the exhaustion of natural resources, poverty, and overpopulation, but rather as an element in the general framework of sustainable development, since all these issues must be addressed to guarantee the establishment of a stable and livable society.&lt;br /&gt;
In particular, it is important to be aware that any technological solution to the energy problem (as well as to, e.g., agricultural production levels) will only mean temporary relief if population growth is not controlled.&lt;br /&gt;
The latter issue should therefore receive top priority in any effort to attain sustainable development.&lt;br /&gt;
&lt;br /&gt;
Whatever the case may be, energy generation in the near future will most likely be based on a mix of many options, that will vary in accord with  local economic, environmental, and social conditions.&lt;br /&gt;
&lt;br /&gt;
== Energy generation in the future ==&lt;br /&gt;
&lt;br /&gt;
As hinted at above, it appears desirable to significantly reduce our dependence on fossil fuels, due to the effect of the burning of fossil fuels on the global climate, contamination, and the accompanying loss of valuable resources (e.g., plastics).&lt;br /&gt;
&lt;br /&gt;
What alternatives are available? A host of methods for energy generation exists that do not depend on fossil fuels. Among the primary such sources are wind energy, solar energy, and hydroelectric energy. Other sources, such as geothermal energy and wave energy, are and probably will remain quantitatively less important, or compete with food supply, as is the case with biofuels.&lt;br /&gt;
&lt;br /&gt;
Hydroelectric energy is a potential &#039;base load&#039; energy source, meaning that it is, or can be, available permanently and on demand. However, this energy source is only available at relatively few locations where the orography and climate is suitable.&lt;br /&gt;
&lt;br /&gt;
Wind and solar energy are potentially plentiful, but strongly dependent on local weather. Therefore, they are not generally considered to be &#039;base load&#039; energy sources, and can only serve to supplement other reliable energy sources. Energy generation should not be interrupted on a cloudy, windless winter&#039;s day! Combinations of various distinct power sources could mitigate this problem somewhat, but it is unlikely that it can be eliminated.&lt;br /&gt;
&lt;br /&gt;
Nuclear fission power is an alternative that does not contribute to the greenhouse effect and serves as base load power supply, but suffers from problems associated with nuclear waste storage and processing, and public acceptance. &lt;br /&gt;
&lt;br /&gt;
Therefore, the search for a base load power source for the future is still an unresolved issue.&lt;br /&gt;
The discovery of a method to store energy on a large scale would completely change the picture, and enhance the viability of solar and wind energy; but currently, no such method is available.&amp;lt;ref&amp;gt;[[:Wikipedia:Grid_energy_storage]]&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== Fusion as an energy option ==&lt;br /&gt;
&lt;br /&gt;
Fusion undoubtedly offers some important advantages. &lt;br /&gt;
&amp;lt;ref&amp;gt;F.F. Chen, &#039;&#039;An Indispensable Truth: How Fusion Power Can Save the Planet&#039;&#039;, {{ISBN|1441978194}}&amp;lt;/ref&amp;gt;&lt;br /&gt;
Once operative, energy supply would be virtually limitless; greenhouse gas exhaust would be zero; nuclear waste and the danger of nuclear accidents would be strongly reduced (with respect to fission power plants), and nuclear proliferation problems would be small or non-existent. On the other hand, there are complications due to the very complex technology required and the radioactive activation of the reactor vessel components.&lt;br /&gt;
A significant part of the latter complications are due to the projected use of D-T fuels (deuterium-tritium) in the first-generation fusion power plants, which is the fuel that is easiest to ignite, but which leads to intense neutron radiation. One may speculate that, if successful, a second generation of fusion power plants can be developed that runs on other fuel mixtures (such as D-D), leading to a reduction of the problems associated with radioactivity.&lt;br /&gt;
&lt;br /&gt;
Differing from some other energy options, the implementation of energy generation by fusion is not immediate, and subject to the solution of a number of technical problems. The current consensus is that while the technical challenges are formidable, they can be overcome. Thus, the main discussion regarding fusion as an energy option is not about its technical feasibility, but about the timescales for implementation.&lt;br /&gt;
&amp;lt;ref&amp;gt;[http://dx.doi.org/10.1016/j.fusengdes.2005.08.015 C. LLewellyn Smith, Fusion Engineering and Design &#039;&#039;&#039;74&#039;&#039;&#039;, Issues 1-4 (2005) 3-8]&amp;lt;/ref&amp;gt;&lt;br /&gt;
While increased investment and improved focus of the current research efforts can certainly help to speed up progress, even under optimal conditions the time needed to achieve the first delivery of fusion-produced energy  to the electricity grid is considerable, and it is unlikely that fusion can contribute to solving the short-term energy crisis (in the coming decades). Fusion must therefore be considered an energy option for the medium to long term.&lt;br /&gt;
&lt;br /&gt;
==See also==&lt;br /&gt;
&lt;br /&gt;
* [[:Wikipedia:Timeline of nuclear fusion|Timeline of nuclear fusion]]&lt;br /&gt;
* [[:Wikipedia:Fusion power|Fusion power reactor]]&lt;br /&gt;
* The [[ITER]] project&lt;br /&gt;
* [[Stellarator reactor]]&lt;br /&gt;
* [[Neutronics in Fusion]]&lt;br /&gt;
&lt;br /&gt;
==References==&lt;br /&gt;
&amp;lt;references /&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8519</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8519"/>
		<updated>2026-02-04T22:08:27Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* See also */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Useful GitHub Repositories for Neutronics in Nuclear Fusion ==&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – Provides Python tools to generate parametric tokamak neutron sources for Monte Carlo transport codes such as OpenMC and MCNP, based on plasma profiles and fusion reaction distributions. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== See Also ==&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, 2004.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast‑ion D‑alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET‑C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7‑X: effect of magnetic configuration,” arXiv:2009.02925, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), &#039;&#039;MCNP User’s Manual – Code Version 6.2&#039;&#039;, Los Alamos National Laboratory, LA-UR-17-29981.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &#039;&#039;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., &#039;&#039;OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., &#039;&#039;Features of Particle and Heavy Ion Transport Code System (PHITS)&#039;&#039;, Journal of Nuclear Science and Technology.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8518</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8518"/>
		<updated>2026-02-04T22:04:00Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: /* See also */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Useful GitHub Repositories for Neutronics in Nuclear Fusion ==&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – Provides Python tools to generate parametric tokamak neutron sources for Monte Carlo transport codes such as OpenMC and MCNP, based on plasma profiles and fusion reaction distributions. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== See also ==&lt;br /&gt;
* [[Nuclear fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, 2004.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast‑ion D‑alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET‑C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7‑X: effect of magnetic configuration,” arXiv:2009.02925, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), &#039;&#039;MCNP User’s Manual – Code Version 6.2&#039;&#039;, Los Alamos National Laboratory, LA-UR-17-29981.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &#039;&#039;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., &#039;&#039;OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., &#039;&#039;Features of Particle and Heavy Ion Transport Code System (PHITS)&#039;&#039;, Journal of Nuclear Science and Technology.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8517</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8517"/>
		<updated>2026-02-04T22:02:41Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Useful GitHub Repositories for Neutronics in Nuclear Fusion ==&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – Provides Python tools to generate parametric tokamak neutron sources for Monte Carlo transport codes such as OpenMC and MCNP, based on plasma profiles and fusion reaction distributions. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== See also ==&lt;br /&gt;
* [[Nuclear Fusion]]&lt;br /&gt;
* [[TECNO FUS]]&lt;br /&gt;
* [[Breeding blanket]]&lt;br /&gt;
* [[Fusion databases]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, 2004.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast‑ion D‑alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET‑C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7‑X: effect of magnetic configuration,” arXiv:2009.02925, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), &#039;&#039;MCNP User’s Manual – Code Version 6.2&#039;&#039;, Los Alamos National Laboratory, LA-UR-17-29981.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &#039;&#039;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., &#039;&#039;OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., &#039;&#039;Features of Particle and Heavy Ion Transport Code System (PHITS)&#039;&#039;, Journal of Nuclear Science and Technology.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
	<entry>
		<id>http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8516</id>
		<title>Neutronics in Fusion</title>
		<link rel="alternate" type="text/html" href="http://wiki.fusenet.eu/fusionwiki/index.php?title=Neutronics_in_Fusion&amp;diff=8516"/>
		<updated>2026-01-30T08:26:35Z</updated>

		<summary type="html">&lt;p&gt;Hasan Ghotme: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Neutronics in fusion deals with the behavior and effects of neutrons produced during fusion reactions. In fusion systems, especially in deuterium–tritium reactions, high-energy neutrons (about 14.1 MeV) are generated in large numbers. These neutrons carry most of the fusion energy and interact with the surrounding materials, where their energy is deposited through scattering and nuclear reactions. Neutronics analysis is therefore essential for predicting energy deposition, material damage, radiation shielding requirements, and tritium breeding performance. Understanding neutronics is a key aspect of designing safe, efficient, and sustainable fusion reactors.&lt;br /&gt;
&lt;br /&gt;
== Fusion Reactions ==&lt;br /&gt;
&lt;br /&gt;
The principal nuclear fusion reactions of interest in fusion energy are summarized below, showing their reaction channels and total energy release (Q-value).&lt;br /&gt;
&lt;br /&gt;
[[File:nuclear_fusion.jpg|thumb|right|350px|D–T Nuclear Fusion Reaction. Source: &#039;&#039;Neutron Sources&#039;&#039;, [https://www.nuclear-power.com/nuclear-power/reactor-physics/atomic-nuclear-physics/fundamental-particles/neutron/neutron-sources/]]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Reaction&lt;br /&gt;
! Q-value (MeV)&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{H} \longrightarrow {}^{4}\mathrm{He} + n&amp;lt;/math&amp;gt; (14.1 MeV)  &lt;br /&gt;
|   17.6&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{He} + n&amp;lt;/math&amp;gt; (2.45 MeV)  &lt;br /&gt;
|   3.27&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{2}\mathrm{H} \longrightarrow {}^{3}\mathrm{H} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 4.03&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{2}\mathrm{H} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 18.3&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle {}^{3}\mathrm{He} + {}^{3}\mathrm{He} \longrightarrow {}^{4}\mathrm{He} + 2p&amp;lt;/math&amp;gt;&lt;br /&gt;
| 12.86&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;math&amp;gt;\displaystyle p + {}^{11}\mathrm{B} \longrightarrow 3\,{}^{4}\mathrm{He}&amp;lt;/math&amp;gt;&lt;br /&gt;
| 8.68&lt;br /&gt;
|-&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Interactions in Fusion Devices ==&lt;br /&gt;
&lt;br /&gt;
Neutrons are electrically neutral and are not influenced by magnetic fields. As a result, fusion neutrons escape the plasma and interact with reactor materials, producing heat and affecting material behavior. The principal neutron interactions in fusion reactors are summarized below:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Interaction&lt;br /&gt;
! Effect &lt;br /&gt;
|-&lt;br /&gt;
| Radiation Damage&lt;br /&gt;
| Causes atomic displacements and transmutation (He, H), degrading mechanical properties such as strength and ductility&lt;br /&gt;
|-&lt;br /&gt;
| Activation&lt;br /&gt;
| Transforms stable materials into radioactive isotopes, affecting maintenance, waste management, and radiation exposure&lt;br /&gt;
|-&lt;br /&gt;
| Tritium Breeding&lt;br /&gt;
| Neutrons react with lithium to produce tritium &amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;/&amp;gt;:&lt;br /&gt;
&amp;lt;ul&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{6}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} \; (+4.78\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;li&amp;gt;&amp;lt;math&amp;gt;\displaystyle {}^{7}\mathrm{Li} + n \longrightarrow {}^{4}\mathrm{He} + {}^{3}\mathrm{H} + n \; (-2.47\ \mathrm{MeV})&amp;lt;/math&amp;gt;&amp;lt;/li&amp;gt;&lt;br /&gt;
&amp;lt;/ul&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Because tritium is extremely rare in nature (half-life ≈ 12.3 years), fusion reactors are initially supplied with tritium from existing stockpiles (primarily from CANDU fission reactors), after which tritium is continuously bred from lithium within the reactor blanket to sustain operation&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;/&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling in Plasma Codes ==&lt;br /&gt;
&lt;br /&gt;
Neutronics simulation plays a fundamental role in the advancement of nuclear fusion by supporting reactor design, safety assessment, and material optimization. The following plasma modeling codes are used to predict fast-ion behavior and fusion-born neutron emission in tokamak and stellarator plasmas, providing neutron source distributions for transport simulations and diagnostic design.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Plasma Code&lt;br /&gt;
! Description and Typical Applications&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp TRANSP]&lt;br /&gt;
| Models plasma conditions and fast-ion dynamics in tokamaks; outputs are used as neutron source terms for transport simulations &amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ipp-garching/fidasim FIDASIM]&lt;br /&gt;
| Simulates fast-ion behavior and predicts fusion-born neutron emission; used to estimate signals for neutron diagnostics like cameras and spectrometers &amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://w3.pppl.gov/transp NUBEAM]&lt;br /&gt;
| Module of TRANSP that models fast-ion distributions from neutral beam injection and fusion reactions; computes neutron source profiles &amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/ascot-code/ascot ASCOT] &lt;br /&gt;
| Monte Carlo orbit-following codes for fast ions in tokamaks and stellarators; predict localized neutron emission patterns to aid diagnostic design and calibration &amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;/&amp;gt;&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Neutron Modeling Using Monte Carlo Neutronics Codes ==&lt;br /&gt;
&lt;br /&gt;
Monte Carlo neutron transport codes are widely used in fusion research to model neutron behavior, material interactions, and diagnostic responses. The table below summarizes the principal neutron-related work performed by each code, together with representative references.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; &lt;br /&gt;
! Code&lt;br /&gt;
! Neutron-Related Work in Fusion&lt;br /&gt;
|-&lt;br /&gt;
| [https://mcnp.lanl.gov MCNP]&lt;br /&gt;
| Neutron transport from plasma to reactor components; shielding design; nuclear heating; activation analysis; neutron diagnostics response modeling &amp;lt;ref name=&amp;quot;MCNP&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://serpent.vtt.fi Serpent]&lt;br /&gt;
| Neutron transport and spectral analysis in fusion blankets; tritium breeding ratio (TBR) calculations; activation and decay heat studies &amp;lt;ref name=&amp;quot;Serpent&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://phits.jaea.go.jp PHITS]&lt;br /&gt;
| Coupled neutron and charged-particle transport; detailed 3D neutronics; radiation damage indicators (DPA, gas production); shielding studies &amp;lt;ref name=&amp;quot;PHITS&amp;quot;/&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| [https://github.com/openmc-dev/openmc OpenMC]&lt;br /&gt;
| High-fidelity neutron transport in complex 3D fusion geometries; neutron diagnostics scoping; activation analysis; uncertainty and sensitivity studies &amp;lt;ref name=&amp;quot;OpenMC&amp;quot;/&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Useful GitHub Repositories for Neutronics in Nuclear Fusion ==&lt;br /&gt;
&lt;br /&gt;
Several GitHub repositories provide tools and workflows that are highly valuable for neutronics development in fusion research:&lt;br /&gt;
&lt;br /&gt;
# &#039;&#039;&#039;fusion-energy&#039;&#039;&#039; – This is a massive and highly recommended GitHub organization for any neutron physicist working in fusion. It hosts a wide range of projects for fusion neutronics and contains tools like fusion_neutron_utils, fusion_neutronics_workflow, and OpenMC plasma source utilities. These projects enable neutron source generation, Monte Carlo transport simulations, activation and decay analysis, and 3D modeling of fusion device neutronics, making it an indispensable resource for both research and development (GitHub: https://github.com/fusion-energy).&lt;br /&gt;
# &#039;&#039;&#039;aurora-multiphysics / aurora&#039;&#039;&#039; – Integrates neutron transport with multiphysics solvers, allowing simulation of neutron energy deposition, radiation effects, and thermal feedback in complex reactor geometries. (GitHub: https://github.com/aurora-multiphysics/aurora)&lt;br /&gt;
# &#039;&#039;&#039;Fusion-Power-Plant-Framework / tokamak-neutron-source&#039;&#039;&#039; – Provides Python tools to generate parametric tokamak neutron sources for Monte Carlo transport codes such as OpenMC and MCNP, based on plasma profiles and fusion reaction distributions. (GitHub: https://github.com/Fusion-Power-Plant-Framework/tokamak-neutron-source)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;references&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&amp;lt;ref name=&amp;quot;BreedingBlanket&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Breeding blanket,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Breeding_blanket&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TritiumCANDU&amp;quot;&amp;gt;&lt;br /&gt;
&amp;quot;Tritium production in CANDU reactors,&amp;quot; *Wikipedia*, https://en.wikipedia.org/wiki/Tritium#Production&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPneutron&amp;quot;&amp;gt;&lt;br /&gt;
A. Sperduti et al., “Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak,” *Plasma Physics and Controlled Fusion*, vol. 63, no. 1, 2021.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;TRANSPsource&amp;quot;&amp;gt;&lt;br /&gt;
“Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET,” *Fusion Engineering and Design*, vol. 136, 2018.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;NUBEAM&amp;quot;&amp;gt;&lt;br /&gt;
A. Pankin et al., “The tokamak Monte Carlo fast ion module NUBEAM in the National Transport Code Collaboration library,” *Computer Physics Communications*, vol. 159, 2004.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;FIDASIM&amp;quot;&amp;gt;&lt;br /&gt;
B. Geiger, L. Stagner, W. W. Heidbrink et al., “Progress in modelling fast‑ion D‑alpha spectra and neutral particle analyzer fluxes using FIDASIM,” *Plasma Physics and Controlled Fusion*, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTneutron&amp;quot;&amp;gt;&lt;br /&gt;
H. Weisen, P. Sirén, J. Varje &amp;amp; JET Contributors, “Comparison of JET‑C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes,” *Nuclear Fusion*, vol. 62, 016017, 2022.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;ASCOTfurth&amp;quot;&amp;gt;&lt;br /&gt;
J. Kontula et al., “ASCOT simulations of 14 MeV neutron rates in W7‑X: effect of magnetic configuration,” arXiv:2009.02925, 2020.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;MCNP&amp;quot;&amp;gt;&lt;br /&gt;
C. J. Werner (ed.), &#039;&#039;MCNP User’s Manual – Code Version 6.2&#039;&#039;, Los Alamos National Laboratory, LA-UR-17-29981.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;Serpent&amp;quot;&amp;gt;&lt;br /&gt;
J. Leppänen et al., &#039;&#039;The Serpent Monte Carlo Code: Status, Development and Applications in Fusion Neutronics&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;OpenMC&amp;quot;&amp;gt;&lt;br /&gt;
P. K. Romano et al., &#039;&#039;OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development&#039;&#039;, Annals of Nuclear Energy.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;lt;ref name=&amp;quot;PHITS&amp;quot;&amp;gt;&lt;br /&gt;
T. Sato et al., &#039;&#039;Features of Particle and Heavy Ion Transport Code System (PHITS)&#039;&#039;, Journal of Nuclear Science and Technology.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&amp;lt;/references&amp;gt;&lt;/div&gt;</summary>
		<author><name>Hasan Ghotme</name></author>
	</entry>
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