1. The Neutron-Gamma Pulse Shape Discrimination of CLLB Detector.
- Author
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Song, Ruiqiang, Peng, Shuo, Tong, Yufeng, Wu, Qi, Qian, Sen, Wang, Zhigang, and Han, Jifeng
- Subjects
PARTICLE detectors ,GAMMA rays ,NEUTRONS ,ARTIFICIAL neural networks ,IMAGE recognition (Computer vision) - Abstract
C
s2 LiLaBr6 : Ce (CLLB) scintillator with the size of Φ 21mm × 25 mm coupled with PMT was used to detect neutron and gamma rays. The pulse shape discrimination (PSD) of neutrons and gamma rays by charge comparison method, the neutrons and gamma rays from AmBe source and fast neutron beam can be separated with figure-of-merit (FOM) values of 0.9 and 1.3, respectively. However, some neutron and gamma rays are difficult to distinguish, so new algorithms need to be investigated to improve the PSD performance of neutron and gamma. Artificial neural networks (ANN) have a very good image recognition capability, thus the ANN model was constructed to discriminate the waveforms of neutron and gamma rays. After ANN model training, the neutron and gamma signals of the CLLB detector were recognized with an accuracy of 98%, and the FOM value of the ANN method was calculated to be 19.4. This result is much higher than the charge comparison method, indicating better discrimination between neutrons and gamma rays with the ANN method. [ABSTRACT FROM AUTHOR]- Published
- 2024
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