BiOBr nanosheets coupling with biomass carbon derived from locust leaves for enhanced photocatalytic degradation of rhodamine B

被引:0
|
作者
Wang, Hongtao [1 ]
Fan, Xiangrui [1 ]
Yan, Mingming [3 ]
Guo, Tianyu [1 ,2 ]
Li, Xingfa [1 ]
Chen, Chao [2 ]
Qi, Yu [1 ]
机构
[1] Taiyuan Univ Technol, Coll Environm Sci & Engn, Jinzhong 030600, Peoples R China
[2] China Inst Radiat Protect, Minist Environm Dept, Taiyuan 030006, Peoples R China
[3] Petrochina Coalbed Methane Co Ltd, Xinzhou Branch, Xinzhou 036600, Peoples R China
基金
中国国家自然科学基金;
关键词
Degradation; Rhodamine B; Adsorption; BiOBr; Renewable energy; IN-SITU SYNTHESIS; HETEROJUNCTION; PHOTODEGRADATION; CONSTRUCTION; PERFORMANCE; RHB;
D O I
10.1016/j.cjche.2024.07.004
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
A series of BiOBr@biomass carbon derived from locust leaves materials (BiOBr@BC) were fabricated and the photocatalytic property was investigated for photocatalytic degradation of rhodamine B (RhB) under visible light. The morphology, structure and photoelectrochemical properties of the photocatalysts were characterized by means of SEM, TEM, XRD, XPS, FT-IR, BET, PL, UV-vis/DRS, and EIS techniques. The results showed that the introduction of BC significantly enhanced the photocatalytic activity. When the content of biomass carbon (BC) in a composite is 3% (based on the mass of BiOBr), the obtained BiOBr@BC-3 exhibits excellent photocatalytic activity, degrading 99% of RhB within 20 min. The excellent degradation efficiency after the introduction of BC can be attributed to the enhanced visible light absorption, narrower band gap, and fast electron-hole pair separation rate. The photocatalytic mechanism on the degradation of RhB was illustrated based on the radicals' trapping experiments and semiconductor energy band position. The proposed material is expected to be of significant application value in the field of wastewater treatment.<br /> (c) 2024 The Chemical Industry and Engineering Society of China, and Chemical Industry Press Co., Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:31 / 43
页数:13
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