Adsorption of thorium (IV) ions using a novel borate-based nano material Ca3Y2B4O12: Application of response surface methodology and Artificial Neural Network

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dc.authoridKaptanoğlu, İkbal Gözde/0000-0002-3852-9853
dc.authorwosidKaptanoğlu, İkbal Gözde/DJX-7946-2022
dc.contributor.authorKaynar, Umit H.
dc.contributor.authorKaptanoglu, I. . Gozde
dc.contributor.authorCam-Kaynar, Sermin
dc.contributor.authorUgurlu, Onur
dc.contributor.authorYusan, Sabriye
dc.contributor.authorAytas, Sule
dc.contributor.authorMadkhli, A. Y.
dc.date.accessioned2023-03-22T19:47:20Z
dc.date.available2023-03-22T19:47:20Z
dc.date.issued2023
dc.departmentBelirleneceken_US
dc.description.abstractSince nuclear wastes are the most important wastes in terms of health and the environment, they are evaluated differently within nuclear reactors as well as in terms of their use in medical and industrial applications. In some cases, emergency intervention is necessary due to the amount of radioactivity or the physical and/or chemical conditions. . The purpose of this study is to investigate the adsorption properties of nano Ca3Y2B4O12 (CYBO) material synthesized by the sol-gel combustion method for the adsorption of Thorium (IV) from an aqueous medium. We tested how pH (3???8), the concentration of Th (IV) (25???125 mg/L), amount of adsorbent value (0.005???0.08 g) and temperature (20???60 ???C), affect adsorption efficiency. The best possible combinations of these parameters were examined by Response Surface Methodology (RSM) and Artificial Neural Network (ANN). R2 values for RSM and ANN were 0.9964 and 0.9666, respectively. According to the models, the adsorption capacity under the optimum conditions determined for the RSM and ANN model was found to be 134.62 mg/g and 125.12 mg/g, respectively.en_US
dc.identifier.doi10.1016/j.apradiso.2022.110606
dc.identifier.issn0969-8043
dc.identifier.issn1872-9800
dc.identifier.pmid36549178en_US
dc.identifier.scopus2-s2.0-85144351001en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.urihttps://doi.org/10.1016/j.apradiso.2022.110606
dc.identifier.urihttps://hdl.handle.net/20.500.14034/631
dc.identifier.volume192en_US
dc.identifier.wosWOS:000904000100011en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.journalApplied Radiation And Isotopesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAdsorptionen_US
dc.subjectThorium (IV)en_US
dc.subjectNano CYBOen_US
dc.subjectModellingen_US
dc.subjectOptimizationen_US
dc.subjectAqueous-Solutionen_US
dc.subjectUranium Vien_US
dc.subjectRemovalen_US
dc.subjectOptimizationen_US
dc.subjectSorptionen_US
dc.subjectNanomaterialsen_US
dc.subjectCarbonen_US
dc.subjectTh(Iv)en_US
dc.subjectRsmen_US
dc.subjectNanocompositeen_US
dc.titleAdsorption of thorium (IV) ions using a novel borate-based nano material Ca3Y2B4O12: Application of response surface methodology and Artificial Neural Networken_US
dc.typeArticleen_US

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