Neutron detection and ?-ray suppression using artificial neural networks with the liquid scintillators BC-501A and BC-537
Küçük Resim Yok
Tarih
2019
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier B.V.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this work we present a comparison between the two liquid scintillators BC-501A and BC-537 in terms of their performance regarding the pulse-shape discrimination between neutrons and ? rays. Special emphasis is put on the application of artificial neural networks. The results show a systematically higher ?-ray rejection ratio for BC-501A compared to BC-537 applying the commonly used charge comparison method. Using the artificial neural network approach the discrimination quality was improved to more than 95% rejection efficiency of ? rays over the energy range 150 to 1000 keV for both BC-501A and BC-537. However, due to the larger light output of BC-501A compared to BC-537, neutrons could be identified in BC-501A using artificial neural networks down to a recoil proton energy of 800 keV compared to a recoil deuteron energy of 1200 keV for BC-537. We conclude that using artificial neural networks it is possible to obtain the same ?-ray rejection quality from both BC-501A and BC-537 for neutrons above a low-energy threshold. This threshold is, however, lower for BC-501A, which is important for nuclear structure spectroscopy experiments of rare reaction channels where low-energy interactions dominates. © 2018
Açıklama
Anahtar Kelimeler
BC-501A, BC-537, Digital pulse-shape discrimination, Fast-neutron detection, Liquid scintillator, Neural networks
Kaynak
Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
WoS Q Değeri
Q3
Scopus Q Değeri
Q1
Cilt
916
