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Home > Press > Iranians Present Model to Predict Photocatalytic Process in Removal of Pollutants

Abstract:
Iranian chemists studied the process of elimination of organic pollutants by using nanophotocatalysts and presented a mathematical model.

Iranians Present Model to Predict Photocatalytic Process in Removal of Pollutants

Tehran, Iran | Posted on October 30th, 2014

The model would be very useful in designing the processes with high efficiency to purify wastewater and waters contaminated with organic pollutants at semi-industrial and industrial scales.

Advanced Oxidation Processes (AOPs) with the use of titanium dioxide and zinc oxide nanoparticles under ultraviolet radiation are among advanced processes that can eliminate resistant organic materials from the environment. In every chemical process, it is very important to precisely understand the mechanism, the reactions and the kinetics of the reaction. The aim of the research was to develop kinetic model of the reaction to predict the yield of removal of organic pollutants from the environment by using nanophotocatalysts.

Among the achievements of the research, mention can be made of the ability to detect reactions during the process of the elimination of resistant organic materials from the environment by using nanophotocatalysts and the ability to optimize effective operational parameters in the process.

According to Dr. Alireza Amani Qadim, one of the researchers, the developed kinetic model is able to precisely predict the performance of the process as a function of the amount of nanophotocatalyst, initial concentration of pollutants, intensity of the radiated light and the process time.

The researcher explained how the objectives of the research were achieved, and said, "In this project, we studied effective parameters in the process of removal of the model pollutant and the kinetic indices of the process. Then, we developed a new kinetic model by using the results to predict the efficiency of the removal of pollutants by using zinc oxide nanoparticles. The performance of the developed model was investigated by using artificial neural networks. Results confirmed the accuracy of the kinetic model."

Results of the research have been published in Applied Catalysis B: Environemtnal, vol. 163, issue 1, 2015, pp. 539-546.

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