Pulse shape discrimination in an organic scintillation phoswich detector using machine learning techniquesopen access
- Authors
- Lee, Yujin; Kim, Jinyoung; Koh, Byoung-Cheol; Yoon, Young Soo; Ha, Chang Hyon
- Issue Date
- Mar-2024
- Publisher
- Frontiers Media SA
- Keywords
- dark matter; gamma spectroscopy; machine learning; organic scintillator; phoswich; pulse shape discrimination
- Citation
- Frontiers in Physics, v.12
- Journal Title
- Frontiers in Physics
- Volume
- 12
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/73385
- DOI
- 10.3389/fphy.2024.1361608
- ISSN
- 2296-424X
- Abstract
- We developed machine learning algorithms for distinguishing scintillation signals from a plastic-liquid coupled detector known as a phoswich. The challenge lies in discriminating signals from organic scintillators with similar shapes and short decay times. Using a single-readout phoswich detector, we successfully identified γ radiation signals from two scintillating components. Our Boosted Decision Tree algorithm demonstrated a maximum discrimination power of 3.02 ± 0.85 standard deviation in the 950 keV region, providing an efficient solution for self-shielding and enhancing radiation detection capabilities. Copyright © 2024 Lee, Kim, Koh, Yoon and Ha.
- Files in This Item
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- Appears in
Collections - College of Natural Sciences > Department of Physics > 1. Journal Articles
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