Hybrid Homogeneous and HeterogeneousPhotocatalytic Processes for Removal ofTriphenylmethane Dyes: Artificial NeuralNetwork Modeling

摘要

Removal of two triphenylmethane dyes, Acid Fuchsin (AF) and Malachite green (MG), was studied by hybrid advanced oxidation processes of homogeneous (UV/Fe2t/H2O2) and heterogeneous (UV/TiO2_SiO2) photocatalysis. A comparison of various processes for removal of model pollutants was performed. The results showed that the utilizing hybrid photocatalytic processes in the presence of silica leads to rapid removal of pollutants, which may be ascribable to the synergistic influence of produced various radical species. The effects of operational variables were studied on the efficiency of the UV/Fe2t/H2O2/TiO2_SiO2 hybrid process. An artificial neural network (ANN) model was intended to predict the removal efficiency of the UV/Fe2t/H2O2/TiO2_SiO2 hybrid process under different operational conditions. The results indicated that there is a good concurrence between the ANN predicted values and experimental results with a correlation coefficient of 0.9873 and 0.9774 for removal of AF and MG dyes, respectively. The designed neural network model gives a dependable technique for modeling the removal efficiency of the UV/Fe2t/H2O2/TiO2_SiO2 hybrid process. Moreover, the relative significance of each variable was computed based on the input-hidden and hidden-output connection weights of the neural network model. The initial concentration of dyes was the most significant variable in the removal efficiency.