4.8 Review

Density Functional Theory Calculations for Insight into the Heterocatalyst Reactivity and Mechanism in Persulfate-Based Advanced Oxidation Reactions

期刊

ACS CATALYSIS
卷 11, 期 17, 页码 11129-11159

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acscatal.1c03099

关键词

AOPs; DFT; persulfate; catalytic oxidation; descriptor; organic pollutants

资金

  1. Australian Research Council [DP190103548]

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This review highlights recent advances in theoretical simulations for persulfate-based advanced oxidation processes, focusing on catalyst properties, persulfate activation mechanism, and degradation mechanism of organic contaminants. The study also discusses descriptors in computational studies and structure-performance relationships within the field. Challenges and future research focuses of DFT simulations in PS-AOPs are proposed, including evaluation of catalyst properties, elucidation of activation mechanisms, and rational design of on-demand catalysts.
Advanced oxidation processes (AOPs) based on persulfates such as peroxymonosulfate and peroxydisulfate via heterogeneous catalysts have been a research hotspot due to their outstanding performances in removing emerging organic contaminants (OCs). In this Review, we highlight the recent advances in theoretical simulations for persulfate-based AOPs (PSAOPs) using density functional theory (DFT), with the emphasis on the catalyst properties and the mechanism of persulfate activation over a variety of heterogeneous catalysts (including nanocarbons, metals, and metal oxides). Moreover, the properties of OCs and their degradation mechanism by diverse reactive oxygen species investigated by theoretical computations are also summarized. The descriptors in computational studies and the related structure-performance relationships are discussed. Finally, the challenges and future research focuses of DFT simulations in PS-AOPs are proposed, including the evaluation of catalyst properties, elucidation of the persulfate activation mechanism, especially the nonradical pathway, and the rational design of on-demand catalysts.

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