Optimizing Converter Layer and Active Volume Thickness for Gallium Nitride Neutron Detectors

Zhang, Zhongming and Aspinall, Michael (2021) Optimizing Converter Layer and Active Volume Thickness for Gallium Nitride Neutron Detectors. In: 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE, Boston, MA, USA. ISBN 9781728176949

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Abstract

Gallium nitride (GaN) is a direct energy gap semiconductor material with a wide bandgap, high thermal conductivity, high chemical stability, and strong resistance to radiation. It has broad prospects in the application of optoelectronics, high temperature and high power devices, and particle detectors. In this work, an early-stage GaN radiation-hardened neutron detector is described. Monte Carlo simulations using Geant4 10.6 are used to investigate and optimize the converter layers and active volume for the detector and the suggested thickness needed to achieve the highest detection efficiency is given. Further, the gamma rejection ability for GaN has been studied, and the spatial distribution of the partial reaction type of gamma rays with GaN are shown for the first time. This work will aid the design and fabrication of radiation-resistant GaN neutron detectors and will benefit reactor monitoring, high-energy physics experiments, and nuclear fusion research.

Item Type:
Contribution in Book/Report/Proceedings
ID Code:
162618
Deposited By:
Deposited On:
23 Nov 2021 14:40
Refereed?:
No
Published?:
Published
Last Modified:
26 Nov 2021 02:18