材料科学
罗丹明B
纳米棒
纳米复合材料
降级(电信)
异质结
可见光谱
电化学
化学工程
光催化
电极
电泳沉积
电解质
纳米技术
光电子学
催化作用
涂层
电信
生物化学
化学
物理化学
计算机科学
工程类
作者
Mozhgan Gholamveysi,Marzieh Ghodrati,Mitra Mousavi,Anita Parsaei-Khomami,Jahan Bakhsh Ghasemi,Mohammad Mehdi Habibi,Maryam Shekofteh-Gohari,Parviz Norouzi,Xuanhua Li
标识
DOI:10.1016/j.surfin.2023.103146
摘要
Photoelectrocatalysis has been extensively used as one of the most widely known advanced oxidation processes (AOPs) owing to its superiority over photocatalytic systems with regards to the reduced recombination of charge carriers. ZnO demonstrates profound performance in PEC systems, and to overcome the obstacle of its limited visible light utilization, heterojunction formation of transition metal dichalcogenides (TMDs) with this classical semiconductor is proposed. Herein, MoSe2 was introduced onto ZnO nanorods to widen its visible light absorption and consequently boost the PEC ability of the proposed composite in omitting model organic contaminants in water. The as-synthesized nanocomposite was immobilized onto FTO by Electrophoretic deposition (EPD) technique which is then represented as the working electrode in the three-electrode PEC system. The characterization of the proposed nanocomposite was attained by techniques including: XRD, FESEM, FTIR, DRS and EDX. Moreover, electrochemical characterization was conducted to study its electrochemical properties. The PEC activity of the samples was studied by the degradation of Rhodamine B dye (62.3%) and tetracycline pharmaceutical (70.2%) under irradiation. The results indicated a much higher PEC ability for ZnO NR/MoSe2/FTO photoelectrode than its bare parent samples as well as its recyclability. To study the impact of the operational parameters, the electrolyte's concentration, initial pH, external bias voltage and initial concentration of the contaminant were investigated. By means of the scavenging tests, electrons and holes have the highest and the lowest importance in the PEC reaction, respectively. The S-scheme mechanism of degradation was proposed based on the cumulative experimental data.
科研通智能强力驱动
Strongly Powered by AbleSci AI