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<p>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 <i>d</i>-band theory by proposing a machine learning-decoded binary descriptor (BD) unifying orbital electronic structure (I<sub>OES</sub>) and orbital geometric structure (I<sub>OGS</sub>) indices to predict PMS activation pathways across diverse coordination environments. This BD framework quantifies antibonding orbital occupancy (via <i>d-p</i> 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 (I<sub>OES</sub> = 0.86, I<sub>OGS</sub> = 0.40) achieved 94.2% <sup>1</sup>O<sub>2</sub> yield and fast kinetics (k<sub>obs</sub> = 1.2 min⁻<sup>1</sup>) toward sulfadiazine degradation. Crucially, a flow-through reactor demonstrated &gt;90% pollutant removal for 30 days at industrial flux (122.3 L m⁻<sup>2</sup> h⁻<sup>1</sup>). This work establishes universal orbital-level design principles for sustainable water remediation, bridging atomic-scale insights to engineering-scale implementation.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月25日

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  • Yifei Wang,
  • Dongyue Liu,
  • Hao Wang,
  • Yuqing Ma,
  • Xuedi Sun,
  • Yiyang Wu,
  • Meng Liu,
  • Yongzhen Peng,
  • Yanbiao Liu

摘要

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.