Heterogeneous Fenton-like systems activated by peroxymonosulfate represent promising platforms for organic wastewater treatment but are significantly hampered by competing adsorption and catalytic oxidation processes at identical active sites. To resolve this critical bottleneck, we develop a diverting dual-site catalyst comprising nitrogen-vacancy (Nv) sites precisely integrated adjacent to iron (Fe) single-atom sites within a carbon nitride framework. This spatially optimized configuration markedly enhances electron mobility and accelerates electron-hole separation under visible-light irradiation, thus enabling the concurrent generation of radical and non-radical oxidizing species. Consequently, the catalytic activity is substantially elevated. Mechanistic insights reveal that Nv sites preferentially anchor pollutants through selective adsorption, while the neighboring Fe sites actively facilitate oxidant activation, establishing a synergistic electron-transfer cascade that significantly boosts pollutant degradation kinetics and catalyst durability across various operational scenarios. Comprehensive experimental analyses coupled with theoretical simulations rigorously validate this dual-site catalytic mechanism. Additionally, life-cycle assessment (LCA) and electrical energy per order (EE/O) evaluations demonstrate the economic viability and reduced environmental impacts of the developed catalyst system. Furthermore, the integration of machine learning methodologies optimizes catalytic performance and elucidates the discrete functional contributions of the dual-site arrangement. Collectively, this work establishes an advanced framework for single-atom catalyst design, paving the way toward sustainable, efficient, and eco-friendly wastewater remediation technologies. This work effectively addresses the long-standing challenge of competitive kinetics in heterogeneous Fenton-like systems through the synergistic interaction between nitrogen vacancies (Nv) and Fe sites on carbon nitride.
Bai et al. (Mon,) studied this question.