Behnaz Sarani - Department of Chemistry, Faculty of Sciences, University of Sistan and Baluchestan, Zahedan ۹۸۱۳۵-۶۷۴, Iran
Mashaallah Rahmani - Department of Chemistry, Faculty of Sciences, University of Sistan and Baluchestan, Zahedan ۹۸۱۳۵-۶۷۴, Iran
Ahmad Reza Abbasian - Department of Materials Engineering, Faculty of Engineering, University of Sistan and Baluchestan, Zahedan, Iran

In this study, we present a new combustion method for the preparation of meso-adsorbent NiFe۲O۴ powders. SEM, XRD, and BET were used for the characterization of adsorbents. BET measurements confirmed a specific surface area (SSA) of ۸۷.۷ m۲.g-۱, a total pore volume (PV) of ۰.۲۳۷۷ cm۳.g-۱, and a mean pore size (PS) of ۱۰.۸۴۱ nm. The mean crystallite diameter of the adsorbent using the Scherrer equation was ۱۰ nm. Also, the response surface methodology and artificial neural network models were used for modeling, optimization, and prediction of responses for removing methyl violet from water and wastewater in lab-scale batches. To study absorption, a four-factor central composite design was used to select the best experimental condition for ultrasonic-assisted adsorption of methyl violet dye. The adjusted R۲ of ۰.۹۹۳۱ and the predicted R۲ of ۰.۹۸۱۳ are very close, indicating the compatibility of the experimental results with the quadratic model. According to the results, optimum conditions were set at an ultrasonic time of ۲۳۱ s, ۱۳.۵ mg of adsorbent, a dye concentration of ۲.۰ mg.L-۱, and a pH = ۷.۹. Also, the learning rule of Levenberg–Marquardt was used for ANN Modeling. According to the proposed ANN, the value of the root mean square error (RMSE) was ۲.۵۶۲, and the value of the correlation coefficient (R۲) was ۰.۹۸۶. Also, removal efficiencies of ۹۶.۸% and ۹۵.۵۷% were obtained for the tap water and wastewater, respectively.

NiFe۲O۴ Meso-adsorbent, Ultrasonic assisted adsorption, Water and wastewater