Malidarre, Roya BoodaghiArslankaya, SeherNar, MelekKirelli, YasinErdamar, Işık Yeşim DicleKarpuz, NurdanDogan, Serap Ozhan2024-04-242024-04-2420222046-01472046-0155https://doi.org/10.1680/jemmr.22.00012https://hdl.handle.net/11468/18673The 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.eninfo:eu-repo/semantics/closedAccessDeep LearningPhy-XPsd SimulationRadiation ShieldingDeep learning prediction of gamma-ray-attenuation behavior of KNN-LMN ceramicsDeep learning prediction of gamma-ray-attenuation behavior of KNN-LMN ceramicsArticle112276282WOS:0009816505000082-s2.0-8512975241610.1680/jemmr.22.00012Q2Q3