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Proceedings Paper

Advances in theoretical models and simulation of electron gain in microchannel plates
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Paper Abstract

As the core component of image intensifier, the electronic multiplication performance of microchannel plate determines the ability of the device to detect weak signals. The theoretical model of electron gain is the theoretical basis for the secondary electron multiplication of microchannel plates. It has important theoretical significance for the research of high performance microchannel plates and image intensifiers. In this paper, the theoretical model and simulation of electron gain in microchannel plates are reviewed. The electronic gain model and the modified theoretical model of the "energy proportional hypothesis" are emphatically introduced. On the basis of the model, some improvements are made and good simulation results are obtained. The behaviors of electron transport, collision and multiplication in microchannels based on the theoretical model of electronic gain and Monte Carlo stochastic calculation method are summarized. The differences among the three models are analyzed, and the problems existing in the theoretical model and simulation of electronic gain at present are analyzed. Finally, aiming at the shortcomings of theoretical model and simulation, the direction of improvement and optimization is put forward.

Paper Details

Date Published: 31 January 2020
PDF: 12 pages
Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 1142736 (31 January 2020);
Show Author Affiliations
Pan Shi, China Building Materials Academy (China)
China Building Materials Guangxin Technology Co., Ltd. (China)
Jinsheng Jia, China Building Materials Academy (China)
Key Lab. of Special Photoelectric Materials in Building Materials Industry (China)
Yang Zhang, China Building Materials Academy (China)
Key Lab. of Special Photoelectric Materials in Building Materials Industry (China)
Bingqiang Zhang, China Building Materials Academy (China)
China Building Material Guangxin Technology Co., Ltd. (China)
Yonggang Huang, China Building Materials Academy (China)
Peng Jiao, China Building Materials Academy (China)
Kangsheng Huang, China Building Materials Academy (China)
China Building Materials Guangxin Technology Co., Ltd. (China)
Yuechong Feng, China Building Materials Academy (China)
China Building Materials Guangxin Technology Co., Ltd. (China)
Sanzhao Wang, China Building Materials Academy (China)
China Building Materials Guangxin Technology Co., Ltd. (China)


Published in SPIE Proceedings Vol. 11427:
Second Target Recognition and Artificial Intelligence Summit Forum
Tianran Wang; Tianyou Chai; Huitao Fan; Qifeng Yu, Editor(s)

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