| Issue |
EPJ Web Conf.
Volume 288, 2023
ANIMMA 2023 – Advancements in Nuclear Instrumentation Measurement Methods and their Applications
|
|
|---|---|---|
| Article Number | 03001 | |
| Number of page(s) | 5 | |
| Section | Fusion Diagnostics and Technology | |
| DOI | https://doi.org/10.1051/epjconf/202328803001 | |
| Published online | 21 November 2023 | |
https://doi.org/10.1051/epjconf/202328803001
Modelling of a SiC Based Detector for the Interpretation of 14.1 MeV Neutrons Measurements
1 Aix-Marseille Univ, Universite´ de Toulon, CNRS, IM2NP, Marseille, France
2 CEA, DES, IRESNE, DER, Cadarache, F-13108, Saint Paul-lez-Durance, France
3 CEA, IRFM, Cadarache, F-13108, Saint-Paul-lez-Durance, France
Published online: 21 November 2023
Wide-bandgap semiconductor-based fast neutron detectors such as silicon carbide (SiC) seem to be a promising concept to meet the implementation requirements as well as the performance specifications for fusion and fission environments such as radiation hardness as well as thermal and mechanical stabilities. Beyond the problem of integration of the device in constrained environments, the issue of the quantitative response of the device in a mixed radiation field must be addressed. Therefore, the characterisation of the detector performances, according to the energy of the neutrons is a key first step needed for neutron detection and monitoring in mixed radiation environments with high levels of gammas and fast and thermal neutron fluxes emissions at large energy scales. This paper presents the interpretation of 14.1 MeV neutron measurements using a numerical model developed with the GEANT4 MonteCarlo transport code. The methodology used for a first attempt to estimate the fluence rate of incident neutrons is exposed and a calculation versus experiment ratio is determined.
Key words: Fast neutrons / Semiconductor Detectors / Silicon Carbide / Radiation Detection
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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