光催化
铋
环境化学
汞元素
烟气
废物管理
化学
无机化学
Mercury(编程语言)
催化作用
环境科学
计算机科学
有机化学
工程类
程序设计语言
作者
Yu Guan,Yinhe Liu,Qiang Lv,Jiang Wu
标识
DOI:10.1016/j.jhazmat.2021.126280
摘要
Photocatalytic oxidation method is a promising technology for solving flue gas mercury (Hg) pollution from industrial plants. Semiconductor photocatalysts have been widely applied in energy conversion and environmental remediation. However, key issues such as low light absorption capacity, wide energy band gap, and poor physicochemical stability severely limit the application of photocatalysts in practical industrial plants. In recent years, bismuth-based (Bi-based) photocatalysts, including bismuth oxide halide BiOX (X = Cl, Br or I), bismuth salt oxymetal BiVO4, and BiOIO3 etc., have increasingly aroused scientists’ attention due to their peculiar crystalline geometric structures, tunable electronic structure and high photocatalytic performance. In present review, we firstly review the photocatalytic reaction mechanism and main photocatalytic oxidation mechanism of mercury. Secondly, the synthetic methods of Bi-based photocatalysts are summarized. Then, according to the mechanism of mercury removal, the experimental modifying approaches including heterojunction making, external atoms doping, defect creating, and crystal face regulating to promote the photocatalytic oxidation of mercury removal are summarized, as well as the determination of the band gap and electronic density of states (DOS) of Bi-based photocatalysts to elucidate the photocatalytic oxidation mechanism via density functional theory (DFT) calculation. Furthermore, constructing electronic transmission channels is an efficient way to improve the photocatalytic activity. Finally, challenges and perspectives of Bi-based photocatalyst for photocatalytic oxidation of mercury removal are presented. In addition, the excellent performance photocatalysts and efficient pollution removal equipment for mercury removal in industrial plants are still required in-depth study.
科研通智能强力驱动
Strongly Powered by AbleSci AI