Environmental Science & Technology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 27, 2025

The competition between radical and nonradical processes in the activated persulfate system is a captivating challenging topic advanced oxidation processes. However, traditional research methods have encountered limitations this area. This study employed DFT combined with machine learning to establish quantitative structure–activity relationship contributions of active species molecular structures pollutants UV system. By comparing models using different input data sets, it was observed that protonation deprotonation organic molecules play crucial role. Additionally, condensed Fukui function, as local descriptor, found be less effective compared dual descriptor due its imprecise definition f0. sulfate exhibits high selectivity toward electrophilic sites on molecules, while global descriptors determined by their chemical properties provide better predictions for contribution rates hydroxyl radicals. Interestingly, there exists piecewise function relating ELU–HO, which further supported experimental data. Currently, cannot explained classical theory requires investigation. Perhaps new perspective brought us combining learning.

Language: Английский