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Author (up) Soderstrom, P.A. et al; Agramunt, J.; Egea, J.; Gadea, A.; Huyuk, T. doi  openurl
  Title Neutron detection and gamma-ray suppression using artificial neural networks with the liquid scintillators BC-501A and BC-537 Type Journal Article
  Year 2019 Publication Nuclear Instruments & Methods in Physics Research A Abbreviated Journal Nucl. Instrum. Methods Phys. Res. A  
  Volume 916 Issue Pages 238-245  
  Keywords BC-501A; BC-537; Digital pulse-shape discrimination; Fast-neutron detection; Liquid scintillator; Neural networks  
  Abstract 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 gamma rays. Special emphasis is put on the application of artificial neural networks. The results show a systematically higher gamma-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 gamma 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 gamma-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.  
  Address [Soderstrom, P-A] ELI NP, Bucharest 077125, Romania, Email: par.anders@eli-np.ro  
  Corporate Author Thesis  
  Publisher Elsevier Science Bv Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0168-9002 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000455016800033 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 3869  
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