Deep learning prediction of gamma-ray-attenuation behavior of KNN-LMN ceramics

Basit Öğe Kaydı
dc.contributor.authorMalidarre, Roya Boodaghi
dc.contributor.authorArslankaya, Seher
dc.contributor.authorNar, Melek
dc.contributor.authorKirelli, Yasin
dc.contributor.authorErdamar, Isk Yesim Dicle
dc.contributor.authorKarpuz, Nurdan
dc.contributor.authorDogan, Serap Ozhan
dc.date.accessioned2024-03-13T10:33:06Z
dc.date.available2024-03-13T10:33:06Z
dc.date.issued2022
dc.departmentİstanbul Beykent Üniversitesien_US
dc.description.abstractThe significance and novelty of the present work is the preparation of non-lead ceramics with the general formula of (1 - x)K0.5Na0.5NbO3-xLaMn(0.5)Ni(0.5)O(3) (KNN-LMN) with different values of x (0 < x < 20) (mol%) to examine the shielding qualities of the KNN-LMN ceramics. This is done by carrying out Phy-X/PSD calculation and predicting the attenuation behavior of the samples by utilizing the deep learning (DL) algorithm. From the attained results, it is seen that the higher the x (concentration of LMN in the KNN-LMN lead-free ceramics), the better the shielding proficiency observed in terms of gamma-shielding performance for the chosen KNN-LMN-based lead-free ceramics. In all sections, good agreement is observed between Phy-X/PSD results and DL predictions.en_US
dc.identifier.doi10.1680/jemmr.22.00012
dc.identifier.endpage282en_US
dc.identifier.issn2046-0147
dc.identifier.issn2046-0155
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85129752416en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage276en_US
dc.identifier.urihttps://doi.org/10.1680/jemmr.22.00012
dc.identifier.urihttps://hdl.handle.net/20.500.12662/3770
dc.identifier.volume11en_US
dc.identifier.wosWOS:000981650500008en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
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.subjectdeep learningen_US
dc.subjectPhy-Xen_US
dc.subjectPSD simulationen_US
dc.subjectradiation shieldingen_US
dc.titleDeep learning prediction of gamma-ray-attenuation behavior of KNN-LMN ceramicsen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu