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Development of an Optimized Converter Layer for a Silicon-Carbide-Based Neutron Sensor for the Detection of Fissionable Materials

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Development of an Optimized Converter Layer for a Silicon-Carbide-Based Neutron Sensor for the Detection of Fissionable Materials. / Monk, Stephen; Platt, Simon; Cheneler, David et al.
2019 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2019. IEEE, 2019.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

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Monk, S, Platt, S, Cheneler, D, Anderson, M & Alhamdi, M 2019, Development of an Optimized Converter Layer for a Silicon-Carbide-Based Neutron Sensor for the Detection of Fissionable Materials. in 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2019. IEEE, 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference , Manchester, United Kingdom, 26/10/19. https://doi.org/10.1109/NSS/MIC42101.2019.9059642

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Vancouver

Monk S, Platt S, Cheneler D, Anderson M, Alhamdi M. Development of an Optimized Converter Layer for a Silicon-Carbide-Based Neutron Sensor for the Detection of Fissionable Materials. In 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2019. IEEE. 2019 doi: 10.1109/NSS/MIC42101.2019.9059642

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Bibtex

@inproceedings{bf32abff409647a79a21e2624633f40f,
title = "Development of an Optimized Converter Layer for a Silicon-Carbide-Based Neutron Sensor for the Detection of Fissionable Materials",
abstract = "We describe the early stage development of a miniature silicon carbide neutron sensor, for applications including robotic monitoring at the Fukushima Daiichi nuclear power plant, specifically, within the primary containment vessel forfuel debris detection and retrieval. Monte Carlo simulations using MCNP 6.2 and Geant4 10.05.01 are used to investigate and optimize converter layers for thermal neutron detection. Performance of a 10B4C:SiC detector system is investigated in detail and a neutron detection efficiency ∼4% is predicted, witha gamma discrimination ratio of the order of 105.",
keywords = "Fukushima Daiichi Nuclear Power Plant, radiation monitoring, neutrons, semiconductor radiation detectors, silicon carbide, Monte Carlo methods",
author = "Stephen Monk and Simon Platt and David Cheneler and Mike Anderson and Mustafa Alhamdi",
year = "2019",
month = oct,
day = "26",
doi = "10.1109/NSS/MIC42101.2019.9059642",
language = "English",
booktitle = "2019 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2019",
publisher = "IEEE",
note = "2019 IEEE Nuclear Science Symposium and Medical Imaging Conference , IEEE NSS/MIC 2019 ; Conference date: 26-10-2019 Through 02-11-2019",

}

RIS

TY - GEN

T1 - Development of an Optimized Converter Layer for a Silicon-Carbide-Based Neutron Sensor for the Detection of Fissionable Materials

AU - Monk, Stephen

AU - Platt, Simon

AU - Cheneler, David

AU - Anderson, Mike

AU - Alhamdi, Mustafa

N1 - Conference code: 26

PY - 2019/10/26

Y1 - 2019/10/26

N2 - We describe the early stage development of a miniature silicon carbide neutron sensor, for applications including robotic monitoring at the Fukushima Daiichi nuclear power plant, specifically, within the primary containment vessel forfuel debris detection and retrieval. Monte Carlo simulations using MCNP 6.2 and Geant4 10.05.01 are used to investigate and optimize converter layers for thermal neutron detection. Performance of a 10B4C:SiC detector system is investigated in detail and a neutron detection efficiency ∼4% is predicted, witha gamma discrimination ratio of the order of 105.

AB - We describe the early stage development of a miniature silicon carbide neutron sensor, for applications including robotic monitoring at the Fukushima Daiichi nuclear power plant, specifically, within the primary containment vessel forfuel debris detection and retrieval. Monte Carlo simulations using MCNP 6.2 and Geant4 10.05.01 are used to investigate and optimize converter layers for thermal neutron detection. Performance of a 10B4C:SiC detector system is investigated in detail and a neutron detection efficiency ∼4% is predicted, witha gamma discrimination ratio of the order of 105.

KW - Fukushima Daiichi Nuclear Power Plant

KW - radiation monitoring

KW - neutrons

KW - semiconductor radiation detectors

KW - silicon carbide

KW - Monte Carlo methods

U2 - 10.1109/NSS/MIC42101.2019.9059642

DO - 10.1109/NSS/MIC42101.2019.9059642

M3 - Conference contribution/Paper

BT - 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2019

PB - IEEE

T2 - 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference

Y2 - 26 October 2019 through 2 November 2019

ER -