Modeling and optimization for adsorption of thorium (IV) ions using nano Gd:ZnO: application of response surface methodology (RSM) and artificial neural network (ANN)

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dc.authoridKaynar, Umit H./0000-0002-3321-0341
dc.authorwosidkaynar, umit H/GOV-3188-2022
dc.contributor.authorKaynar, Ümit Hüseyin
dc.date.accessioned2023-03-22T19:47:32Z
dc.date.available2023-03-22T19:47:32Z
dc.date.issued2022
dc.departmentBelirleneceken_US
dc.description.abstractThe waste problem created by nuclear materials both in nuclear reactors and after their medical and industrial use is evaluated differently from other wastes because they can harm human and environmental health. In this study, it is aimed to study the adsorption properties of Gd ions doped nano ZnO (Gd/nano-ZnO) material synthesized by microwave assisted ignition method for the adsorption of Thorium (IV) from aqueous medium. We tested how pH (3-8), temperature (20-60 degrees C), Th (IV) concentration (25-125 mg/L) and adsorbent amount (0.005-0.08 g) affect adsorption efficiency. The best possible combinations of these parameters were examined by Response Surface Methodology (RSM) and Artificial Neural Network (ANN). R-2 values for RSM and ANN were 0.9970 and 0.9666, respectively. According to the models, the experimental adsorption capacity under the optimum conditions determined for the RSM and ANN model was found to be 192.62 mg/g and 218.47 mg/g, respectively.en_US
dc.description.sponsorshipTurkish Scientific Research Council [120M235, TUBITAK-1001]en_US
dc.description.sponsorshipThis study was supported by the Turkish Scientific Research Council with the project numbered 120M235 within the scope of the TUBITAK-1001 project.en_US
dc.identifier.doi10.1080/24701556.2022.2072345
dc.identifier.issn2470-1556
dc.identifier.issn2470-1564
dc.identifier.scopus2-s2.0-85132677799en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.urihttps://doi.org/10.1080/24701556.2022.2072345
dc.identifier.urihttps://hdl.handle.net/20.500.14034/752
dc.identifier.wosWOS:000790744700001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Incen_US
dc.relation.journalInorganic And Nano-Metal Chemistryen_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 Gden_US
dc.subjectZnOen_US
dc.subjectmodelingen_US
dc.subjectoptimizationen_US
dc.subjectAqueous-Solutionsen_US
dc.subjectRemovalen_US
dc.subjectUranium(Vi)en_US
dc.subjectNanocompositesen_US
dc.subjectNanomaterialsen_US
dc.subjectSorptionen_US
dc.subjectNanoparticlesen_US
dc.subjectCompositesen_US
dc.subjectIsothermsen_US
dc.subjectCompounden_US
dc.titleModeling and optimization for adsorption of thorium (IV) ions using nano Gd:ZnO: application of response surface methodology (RSM) and artificial neural network (ANN)en_US
dc.typeArticleen_US

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