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چکیده
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The chitin, chitin/TiO2 and chitin/TiO2/ZnO composites were prepared to study the removal of methyl orange dye (MO) from aqueous solution. The physicochemical characterization of the chitin, chitin/TiO2/ZnO and chitin/TiO2 nanoparticles was carried out using Fourier transform infrared spectroscopy and scanning electron microscopy. Artifcial neural network (ANN) and response surface methodology (RSM), based on Box–Behnken design, were applied to model the MO removal process. The results of the models were compared with the experimental data. The efect of the main parameters such as catalyst load, solution pH, initial concentration of hydrogen peroxide and initial dye concentration was studied. A good agreement was observed between ANN model predictions and experimental results. The results showed the superiority of the ANN method to describe the nonlinear behavior of the photocatalytic process and the accuracy of the ANN model to predict the target efciency values of MO removal. The efectiveness of all the selected parameters on the removal efciency was expressed through the Pareto analysis. The results using ANN and RSM models showed that the most efective variable in the photocatalytic process is the catalyst load with a relative importance of 38.86% and 25.93% obtained by ANN and RSM, respectively. The chitin/TiO2/ZnO catalyst showed 61% dye removal at 4 h of UV irradiation. The removal efciency of chitin/TiO 2/ZnO catalyst improved in the presence of UV/H2O2.
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