Origins of Selective Oxidation in Carbon-Based Nonradical Oxidation Processes toward Organic Pollutants: Quantitative Structure–Activity Relationships (QSARs)
Metal-free carbon material-mediated nonradical oxidation processes (C-NOPs) have emerged as a research hotspot due to their excellent performance in selectively eliminating organic pollutants in aqueous environments. However, the selective oxidation mechanisms of C-NOPs remain obscure due to the div...
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Veröffentlicht in: | Environmental science & technology 2024-03, Vol.58 (10), p.4781-4791 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Metal-free carbon material-mediated nonradical oxidation processes (C-NOPs) have emerged as a research hotspot due to their excellent performance in selectively eliminating organic pollutants in aqueous environments. However, the selective oxidation mechanisms of C-NOPs remain obscure due to the diversity of organic pollutants and nonradical active species. Herein, quantitative structure–activity relationship (QSAR) models were employed to unveil the origins of C-NOP selectivity toward organic pollutants in different oxidant systems. QSAR analysis based on adsorption and oxidation descriptors revealed that C-NOP selectivity depends on the oxidation potentials of organic pollutants rather than on adsorption interactions. However, the dominance of electronic effects in selective oxidation decreases with increasing structural complexity of organic pollutants. Moreover, the oxidation threshold solely depends on the inherent electronic nature of organic pollutants and not on the reactivity of nonradical active species. Notably, the accuracy of substituent descriptors (Hammett constants) and theoretical descriptors (e.g., highest occupied molecular orbital energy, ionization potential, and single-electron oxidation potential) is significantly influenced by the complexity and molecular state of organic pollutants. Overall, the study findings reveal the origins of organic pollutant-oriented selective oxidation and provide insight into the application of descriptors in QSAR analysis. |
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ISSN: | 0013-936X 1520-5851 1520-5851 |
DOI: | 10.1021/acs.est.3c06252 |