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首页> 外文期刊>Recent Patents on Chemical Engineering >Studies on the Applicability of Artificial Neural Network (ANN) in Evaluation of Photocatalytic Performance of TiO2 thin Film Doped by SiO2
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Studies on the Applicability of Artificial Neural Network (ANN) in Evaluation of Photocatalytic Performance of TiO2 thin Film Doped by SiO2

机译：人工神经网络在SiO2掺杂TiO2薄膜光催化性能评估中的适用性研究

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摘要

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.
机译：采用溶胶-凝胶法在玻璃基板上制备了具有高光催化活性的TiO2和TiO2：SiO2纳米晶膜。然后将膜在500°C进行高温处理，从而导致TiO2晶体生长。之后，将TiO 2：SiO 2膜与甲基橙（MO）的水溶液（10 mg.L〜（-1））接触，并在UV下照射。所得膜显示出高的光催化活性。在当前的研究中，通过人工神经网络（ANN）研究了TiO2晶体的光催化活性。这是通过预测各种SiO2浓度和降解时间中MO的浓度来实现的。为了执行建模，这项工作中使用了多层感知器（MLP）网络，其学习算法是Levenberg-Marquardt（LM）。建模结果表明，仿真结果与从实验中获得的数据之间有着极好的一致性。值得注意的是，在当前的工作中，已经研究了在最近的论文和专利中应用的用于制备纳米晶体膜，确定其光催化性能以及对这些过程进行建模的方法。

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