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基于铁掺杂金属有机框架衍生碳基催化剂的选择性氧化行为:活性位点调控与降解机理分析

Selective oxidation behavior based on iron-doped MOF derived carbon-based catalysts: Active site regulation and degradation mechanism analysis.

作者信息

Chen Zhonglin, Wang Xinhao, Zhang Ming, Liu Chenyong, Li Wenhui, Tian Tian, Wei Wenxian, Qiao Weichuan, Gu Cheng, Li Jiansheng

机构信息

Department of Environmental Engineering, College of Ecology and Environment, Nanjing Forestry University, Nanjing 210037, China.

State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China.

出版信息

J Colloid Interface Sci. 2024 Sep 15;670:323-336. doi: 10.1016/j.jcis.2024.05.035. Epub 2024 May 15.

Abstract

Selective removal of target organic pollutants in complex water quality of municipal sewage is extremely important for the deep treatment of water quality. Here, energetic MOF and Fe-MOF are doped in electrostatic spinning process to adjust the structure and composition of the catalysts, active oxygen species (ROSs), realizing the selective removal of organic pollutants. Non-azo and azo pollutants are selected as target pollutants. Catalysts PCFe-8 with Fe nanoclusters, EPCFe-8 with Fe-N, and EPC-8 without Fe doping are used to activate peroxymonosulfate (PMS) for degrading pollutants. The results show that the PCFe-8/PMS system can produce the most SO and exhibit superior removal of azo pollutants, whereas the degradation behavior of non-azo pollutants is more inclined to occur in the EPCFe-8/PMS system and the EPC-8/PMS system. This work provides a reference for elucidating the relationship between catalyst structure and components, types of ROSs, and selective degradation of pollutants.

摘要

在城市污水复杂水质中选择性去除目标有机污染物对于水质深度处理极为重要。在此,将高能金属有机框架材料(MOF)和铁基金属有机框架材料(Fe-MOF)掺杂于静电纺丝过程中,以调整催化剂的结构和组成、活性氧物种(ROSs),实现有机污染物的选择性去除。选择非偶氮和偶氮污染物作为目标污染物。使用具有铁纳米团簇的催化剂PCFe-8、具有Fe-N的EPCFe-8以及未掺杂铁的EPC-8来活化过一硫酸盐(PMS)以降解污染物。结果表明,PCFe-8/PMS体系能产生最多的SO,并对偶氮污染物表现出卓越的去除效果,而非偶氮污染物的降解行为更倾向于发生在EPCFe-8/PMS体系和EPC-8/PMS体系中。这项工作为阐明催化剂结构与成分、ROSs类型以及污染物选择性降解之间的关系提供了参考。

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