Abstract
The activation of the lattice oxygen oxidation mechanism is vital for enhancing oxygen evolution reaction (OER) performance as it enables direct O–O bond formation, avoiding the *OOH formation. Compared with the conventional adsorbate evolution mechanism (AEM), the lattice oxygen-mediated mechanism (LOM) can break the theoretical limit of conventional adsorbate-based scaling relations and enhance the oxygen evolution reaction kinetics. Thus, there is an urgent need for an efficient strategy for designing OER electrocatalysts based on LOM. The O p band center is employed as descriptor in conjunction with machine learning to facilitate the activation of lattice oxygen. The descriptor can accelerate the catalyst design process as it circumvents the need for complex intermediate calculations. According to predictions, the Fe-Co3O4 catalyst exhibits OER performance comparable to that of noble metal catalysts. The Fe-Co3O4 catalyst achieves a low overpotential of 258 mV at 20 mA cm-2 in 0.5 M H2SO4, attributed to the shift in catalytic mechanism from AEM to LOM.The incorporation of Fe effectively induces an upshift in the O p band center and weakens the Co–O bond, thereby promoting direct O–O coupling for O2 generation and consequently reducing the OER overpotential. Our study introduces a method to activate the lattice oxygen of metal oxide electrocatalysts, holding substantial promise for enhancing large-scale hydrogen production.
| Original language | English |
|---|---|
| Article number | 137224 |
| Journal | Fuel |
| Volume | 406 |
| DOIs | |
| State | Published - 15 Feb 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Electrocatalysts
- Lattice oxygen-mediated mechanism
- Machine learning
- The O p band center
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