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    Adsorption of thorium (IV) ions using a novel borate-based nano material Ca3Y2B4O12: Application of response surface methodology and Artificial Neural Network
    (Pergamon-Elsevier Science Ltd, 2023) Kaynar, Umit H.; Kaptanoglu, I. . Gozde; Cam-Kaynar, Sermin; Ugurlu, Onur; Yusan, Sabriye; Aytas, Sule; Madkhli, A. Y.
    Since 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.
  • Küçük Resim
    Öğe
    Determination of thorium adsorption processes by alpha spectrometry on Co-doped ZnO nano materials; modeling and optimization
    (Springer, 2023) Cam-Kaynar, Sermin; Kaynar, Umit H.
    With increasing environmental problems, it has increased the focus on waste removal and recovery. The objective of this study was to employ Co-doped ZnO nano-material, synthesized using the gel-ignition method, for thorium (IV) adsorption. The adsorbent structure was characterized subsequently, thorium (IV) adsorption was optimized using the Response Rurface Method (RSM). The optimal combination of parameters was determined using the RSM model, where the R-2 and R-Adj(2) values were 0.9908 and 0.9639, respectively, indicating the theoretical and experimental conditions were in harmony. The experimental adsorption capacity of the Co-doped ZnO nanomaterial was found to be 121.29 mg g(-1) under the specified optimum conditions.