Neutron detection and ?-ray suppression using artificial neural networks with the liquid scintillators BC-501A and BC-537

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dc.contributor.authorSöderström P.-A.
dc.contributor.authorJaworski G.
dc.contributor.authorValiente Dobón J.J.
dc.contributor.authorNyberg J.
dc.contributor.authorAgramunt J.
dc.contributor.authorde Angelis G.
dc.contributor.authorGonzález V.
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2019
dc.departmentNiğde ÖHÜ
dc.description.abstractIn 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
dc.description.sponsorshipNational Brain Research Centre Science and Technology Facilities Council European Social Fund Science and Technology Facilities Council Generalitat Valenciana
dc.description.sponsorshipThis work was partially financed by the Swedish Research Council , UK Science and Technology Facilities Council (STFC) under grant numbers ST/J000124/1 , ST/L005727/1 , and ST/L005735/1 , NuSTAR.DA BMBF 05P15RDFN1 , 114F473 for TUBITAK , and the Polish National Research Centre (grants 2017/25/B/ST2/01569 , 2016/22/M/ST2/00269 , 2014/14/M/ST2/00738 ), COPIN-IN2P3 , COPIGAL, POLITA projects . A. Gadea activity has been partially supported by MINECO and Generalitat Valenciana, Spain , grants FPA2014-57196-C5 , Severo Ochoa and PROMETEO II/2014/019 and by the E.C. FEDER funds . G. Jaworski acknowledges the support of the framework of the European Social Fund through the Warsaw University of Technology Development Programme, realized by the Center for Advance Studies. We would also like to thank Mr. A. Grant and Mr. I. Burrows from the STFC Daresbury Laboratory for the CAD drawings used for Fig. 1 .
dc.identifier.doi10.1016/j.nima.2018.11.122
dc.identifier.endpage245
dc.identifier.issn0168-9002
dc.identifier.scopus2-s2.0-85057630109
dc.identifier.scopusqualityQ1
dc.identifier.startpage238
dc.identifier.urihttps://dx.doi.org/10.1016/j.nima.2018.11.122
dc.identifier.urihttps://hdl.handle.net/11480/1520
dc.identifier.volume916
dc.identifier.wosWOS:000455016800033
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthor[0-Belirlenecek]
dc.language.isoen
dc.publisherElsevier B.V.
dc.relation.ispartofNuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectBC-501A
dc.subjectBC-537
dc.subjectDigital pulse-shape discrimination
dc.subjectFast-neutron detection
dc.subjectLiquid scintillator
dc.subjectNeural networks
dc.titleNeutron detection and ?-ray suppression using artificial neural networks with the liquid scintillators BC-501A and BC-537
dc.typeArticle

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