Unified electronic-geometric descriptor deciphers peroxymonosulfate activation using Fe-based dual-atom catalysts

Yifei Wang, Dongyue Liu, Hao Wang, Yuqing Ma, Xuedi Sun, Yiyang Wu, Meng Liu, Yongzhen Peng () and Yanbiao Liu ()
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Yifei Wang: Beijing University of Technology, National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Key Laboratory of Beijing for Water Quality Science and Water Environment Recovery Engineering
Dongyue Liu: Beijing University of Technology, National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Key Laboratory of Beijing for Water Quality Science and Water Environment Recovery Engineering
Hao Wang: Beijing University of Technology, National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Key Laboratory of Beijing for Water Quality Science and Water Environment Recovery Engineering
Yuqing Ma: Beijing University of Technology, National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Key Laboratory of Beijing for Water Quality Science and Water Environment Recovery Engineering
Xuedi Sun: Beijing University of Technology, National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Key Laboratory of Beijing for Water Quality Science and Water Environment Recovery Engineering
Yiyang Wu: Beijing University of Technology, National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Key Laboratory of Beijing for Water Quality Science and Water Environment Recovery Engineering
Meng Liu: Dalian University of Technology, School of Environmental Science and Technology, Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education)
Yongzhen Peng: Beijing University of Technology, National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Key Laboratory of Beijing for Water Quality Science and Water Environment Recovery Engineering
Yanbiao Liu: Dalian University of Technology, School of Environmental Science and Technology, Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education)

Nature Communications, 2025, vol. 16, issue 1, 1-11

Abstract: Abstract The rational design of high-efficiency Fenton-like catalysts remains hindered by insufficient understanding of electronic-geometric synergy in peroxymonosulfate (PMS) activation. We transcend classical d-band theory by proposing a machine learning-decoded binary descriptor (BD) unifying orbital electronic structure (IOES) and orbital geometric structure (IOGS) indices to predict PMS activation pathways across diverse coordination environments. This BD framework quantifies antibonding orbital occupancy (via d-p hybridization) and geometric constraints (interatomic distance/O-H elongation), enabling precise screening of Fe-based dual-atom catalysts (DACs). Among FeM DACs (M = Ti, V, Cr, Mn, Fe, Co, Ni, Cu), FeMn DACs with optimal BD values (IOES = 0.86, IOGS = 0.40) achieved 94.2% 1O2 yield and fast kinetics (kobs = 1.2 min⁻1) toward sulfadiazine degradation. Crucially, a flow-through reactor demonstrated >90% pollutant removal for 30 days at industrial flux (122.3 L m⁻2 h⁻1). This work establishes universal orbital-level design principles for sustainable water remediation, bridging atomic-scale insights to engineering-scale implementation.

Date: 2025
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DOI: 10.1038/s41467-025-65500-w

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