alexa Sensitivity analysis of the photoactivity of Cu-TiO2 ZnO during advanced oxidation reaction by Adaptive Neuro-Fuzzy Selection Technique.
Materials Science

Materials Science

Research & Reviews: Journal of Material Sciences

Author(s): Mohammad Reza Delsouz Khaki, Baharak Sajjadi, Abdul Aziz Abdul Raman, Wan Mohd Ashri Wan Daud, Shahaboddin Shmshirband

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One of the most pivotal limitations of TiO2 or ZnO based lattices is their photocatalysis activity under visible light irradiation. In this study, a hybrid photocatalyst was generated by doping TiO2/ZnO lattice with copper in order to improve their photo-activity. The main aim was to analyse the sensitivity of photoactivity of Cu–TiO2/ZnO toward operating conditions in advanced oxidation reaction for photodegradation of two different dyes under visible light irradiation. The sol–gel-prepared composite was characterized in detail to confirm its properties in terms of band gap, crystalline structure/size, optical absorption and surface area. Then, ANFIS (Adaptive Neuro Fuzzy Inference System) was employed to investigate the effects of five independent variables including dye and catalyst concentrations, pH, intensity of light irradiation and reaction time on the photocatalytic performance of Cu–TiO2/ZnO. This process includes several ways of discovering a subset from the group of the recorded parameters and predicting which variable has the strongest effect on the response of interest. Besides, variable search was performed using the ANFIS network. According to variable selection using ANFIS analysis, catalyst concentration and reaction time were the most effective parameters for MO degradation whereas dye concentration and pH were the most influential factors on MB removal using Cu–TiO2/ZnO. Furthermore, Cu–TiO2/ZnO photocatalyst presented the maximum removal efficiency of: color: 83.35%, COD: 73.54% and TOC: 54.46% for MO degradation and color: 75.50%, COD: 68.00% and TOC: 46.41% for MB degradation.

This article was published in Measurement and referenced in Research & Reviews: Journal of Material Sciences

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