Deep learning prediction for gamma-ray attenuation behavior of the KNN-LMN based lead-free ceramics

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dc.authoridYasin Kırelli / 0000-0002-3605-8621en_US
dc.authorscopusidYasin Kırelli / 57219179532en_US
dc.authorwosidYasin Kırelli / HHC-1961-2022
dc.contributor.authorMalidarre, Roya Boodaghi
dc.contributor.authorArslankaya, Seher
dc.contributor.authorNar, Melek
dc.contributor.authorKırelli, Yasin
dc.contributor.authorKarpuz, Nurdan
dc.contributor.authorÖzhan Doğan, Serap
dc.contributor.authorMalidarreh, Parisa Boodaghi
dc.date.accessioned2022-06-07T08:13:27Z
dc.date.available2022-06-07T08:13:27Z
dc.date.issued2022en_US
dc.departmentİstinye Üniversitesi, İktisadi, İdari ve Sosyal Bilimler Fakültesi, Yönetim Bilişim Sistemleri Bölümüen_US
dc.description.abstractThe significance and novelty of the present work is the preparation of the non-lead ceramic by the general formula of (1-x) K0.5Na0.5NbO3-xLaMn0.5Ni0.5O3 with different x (0<x<20) (mol%) to examine the shielding qualities of KNN-LMN ceramic. This is done using PhyX/PSD calculation and predicts the attenuation behavior of the samples utilizing the Deep Learning (DL) algorithm. From the attained results it is seen that the higher the x (concentration of the LMN in KNN-LMN lead-free ceramics) the better shielding proficiency is observed in terms of gamma shielding performances for chosen KNN-LMN based lead-free ceramics. In all sections, a good agreement is observed between PhyX/PSD results and DL predictions. © 2022 ICE Publishing: All rights reserved.en_US
dc.identifier.citationMalidarre, R. B., Arslankaya, S., Nar, M., Kirelli, Y., Erdamar, I. Y. D., Karpuz, N., . . . Malidarreh, P. B. (2022). Deep learning prediction for gamma-ray attenuation behavior of the KNN-LMN based lead-free ceramics. Emerging Materials Research, doi:10.1680/jemmr.22.00012en_US
dc.identifier.doi10.1680/jemmr.22.00012en_US
dc.identifier.issn2046-0147en_US
dc.identifier.scopus2-s2.0-85129752416en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.urihttps://doi.org/10.1680/jemmr.22.00012
dc.identifier.urihttps://hdl.handle.net/20.500.12713/2821
dc.identifier.wosWOS:000981650500008en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorKırelli, Yasin
dc.language.isoenen_US
dc.publisherICE Publishingen_US
dc.relation.ispartofEmerging Materials Researchen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleDeep learning prediction for gamma-ray attenuation behavior of the KNN-LMN based lead-free ceramicsen_US
dc.typeArticleen_US

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