Pharmaceutical wastewater treatment using TiO2 nanosheets deposited by cobalt co-catalyst as hybrid photocatalysts: combined experimental study and artificial intelligence modeling

IF 1 Q4 ENGINEERING, CHEMICAL Chemical Product and Process Modeling Pub Date : 2023-01-24 DOI:10.1515/cppm-2022-0070
Amin Esmaeili, Salar Heydari Shalmani, Azadeh Ebrahimian Pirbazari, Fatemeh Esmaeili Khalil Saraei, Fatemeh-Sadat Tabatabai-Yazdi, Ali Ebrahimian Pirbazari, Ali Derakhshesh
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Abstract

Abstract In this work, we developed a facile method for photocatalytic deposition of cobalt atoms as co-catalyst on TiO2 nanosheets (Co(x)/T) under visible light instead of UV irradiation for the first time. The deposition of cobalt atoms on TNs in the Co(x)/T samples was confirmed by DRS, Raman spectroscopy, photoluminescence, nitrogen physisorption, and TEM analyses. The size of cobalt nanoparticles/cluster dispersed on the TiO2 nanosheets were in the range of 5–20 nm according to TEM results. The PXRD patterns showed that the crystal structure and the anatase phase of TNs were preserved in the Co(x)/T samples after the visible light-assisted deposition process. The Co(x)/T samples showed higher activity compared to pure TiO2 nanosheets for the visible light degradation of tetracycline (TC) as pharmaceutical pollutant due to presence of cobalt co-catalyst. We studied the effect of several parameters on the degradation process and proposed the mechanism of degradation according to quenching experiments results. Due to time-consuming and costly of experimental works, we designed two strong artificial intelligence (AI) models (artificial neural networks (ANN) and neuro-fuzzy inference systems (ANFIS)) to estimate the removal process of TC, and predict the removal percent of TC for new values of inputs before performing experiment. The experimental and computational studies showed that the fabricated photocatalysts are as promising candidates for industrial wastewater treatment to meet environmental regulations and provide a new avenue for practical implications.
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钴助催化剂沉积TiO2纳米片作为混合光催化剂处理制药废水:实验研究与人工智能建模相结合
摘要在这项工作中,我们首次开发了一种在可见光下而不是紫外线照射下在TiO2纳米片(co(x)/T)上光催化沉积钴原子作为助催化剂的简单方法。通过DRS、拉曼光谱、光致发光、氮物理吸附和TEM分析证实了钴原子在Co(x)/T样品中的TNs上的沉积。根据TEM结果,分散在TiO2纳米片上的钴纳米颗粒/团簇的尺寸在5–20 nm范围内。PXRD图谱显示,在可见光辅助沉积工艺后,在Co(x)/T样品中保留了TNs的晶体结构和锐钛矿相。由于钴助催化剂的存在,与纯TiO2纳米片相比,Co(x)/T样品在可见光降解作为药物污染物的四环素(TC)方面表现出更高的活性。研究了几个参数对降解过程的影响,并根据淬火实验结果提出了降解机理。由于实验工作耗时且成本高昂,我们设计了两个强人工智能(AI)模型(人工神经网络(ANN)和神经模糊推理系统(ANFIS))来估计TC的去除过程,并在进行实验前预测新输入值的TC去除率。实验和计算研究表明,所制备的光催化剂是工业废水处理的有前途的候选者,符合环境法规,并为实际应用提供了新的途径。
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来源期刊
Chemical Product and Process Modeling
Chemical Product and Process Modeling ENGINEERING, CHEMICAL-
CiteScore
2.10
自引率
11.10%
发文量
27
期刊介绍: Chemical Product and Process Modeling (CPPM) is a quarterly journal that publishes theoretical and applied research on product and process design modeling, simulation and optimization. Thanks to its international editorial board, the journal assembles the best papers from around the world on to cover the gap between product and process. The journal brings together chemical and process engineering researchers, practitioners, and software developers in a new forum for the international modeling and simulation community. Topics: equation oriented and modular simulation optimization technology for process and materials design, new modeling techniques shortcut modeling and design approaches performance of commercial and in-house simulation and optimization tools challenges faced in industrial product and process simulation and optimization computational fluid dynamics environmental process, food and pharmaceutical modeling topics drawn from the substantial areas of overlap between modeling and mathematics applied to chemical products and processes.
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