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

The 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.