Abstract
Nanocrystalline films of TiO2 and TiO2:SiO2 with high photocatalytic activity were prepared on glass substrates by the application of sol-gel method. Then the films were subjected to a high temperature treatment at 500°C, which resulted in growth of TiO2 crystals. Afterwards the TiO2:SiO2 films were in contact with an aqueous solution (10 mg.L-1) of methyl orange (MO) and irradiated under UV. The resulted films showed a high photocatalytic activity. In the current study the photocatalytic activity of TiO2 crystals was studied by an Artificial Neural Network (ANN). This was achieved by predicting the concentration of MO in various values of SiO2 concentration and time of degradation. In order to perform the modeling, Multi-layer Perceptron (MLP) network was used in this work, with its learning algorithm being Levenberg-Marquardt (LM). The outcome of modeling showed that there was an excellent agreement between the results of simulation and the data obtained from the experiments. It is worth noting that in the current work, the methods applied in recent papers and patents for the preparation of nanocrystalline films and determination of their photocatalytic performance and also modeling of such processes have been studied.
Keywords: Photocatalytic activity, thin film, Artificial Neural Network, Sol-gel, Multi-layer Perceptron, Simulation
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