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A comprehensive comparison of green Bi2WO6/g-C3N4 and Bi2WO6/TiO2 S-scheme heterojunctions for photocatalytic adsorption/degradation of Cefixime: Artificial neural network, degradation pathway, and toxicity estimation

吸附 光催化 线性扫描伏安法 X射线光电子能谱 异质结 化学 化学工程 材料科学 核化学 光化学 循环伏安法 电化学 催化作用 电极 光电子学 有机化学 工程类 物理化学
作者
Ariya Gordanshekan,Shakiba Arabian,Ali Reza Solaimany Nazar,Mehrdad Farhadian,Shahram Tangestaninejad
出处
期刊:Chemical Engineering Journal [Elsevier]
卷期号:451: 139067-139067 被引量:106
标识
DOI:10.1016/j.cej.2022.139067
摘要

This study comprehensively compared two hydrothermally synthesized S-scheme heterojunctions, Bi2WO6/g-C3N4 and Bi2WO6/TiO2. The photocatalytic removal of cefixime (CFX) was used to screen the different mass ratios of the components for each heterojunction. Photocatalytic adsorption/degradation and operational effects such as initial pH, the ratio of CFX concentration to the photocatalyst load, light intensity, UV irradiation, and the presence of anions were compared and evaluated. The adsorption isotherms and kinetics of the photocatalytic adsorption and degradation were studied. Furthermore, the band structure was investigated by valence band X-ray photoelectron spectroscopy (VB-XPS), Mott-Schottky plot, and UV–vis DRS. The mechanism of the photocatalytic reaction under visible and UV–vis irradiation was comprehensively investigated by scavenger tests and electron spin resonance (ESR). The photocurrent response, EIS, and linear sweep voltammetry (LSV) results confirmed the photocatalytic enhancement of the heterojunctions. The leaching of metal ions, reusability, and performance of the heterojunctions were investigated for 6 cycles. The photocatalytic degradation pathway of CFX and the toxicity of the by-products were investigated by LC-MS and Toxicity Estimation Software Tool (T.E.S.T). After 135 min of photocatalytic reactions, the TOC removal efficiency of CFX was 94 % and 91 % for Bi2WO6/g-C3N4 and Bi2WO6/TiO2. CFX and the by-products were entirely mineralized after 180 min of the reactions. It was found that the binary heterojunctions and the photocatalytic reactions are green and environmentally friendly. The optimized artificial neural network with 18 neurons simulated the experiments. The trained feed-forward network was able to successfully simulate different operating conditions and different mass ratios of the heterojunctions.
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