<p>Lowering the overpotential of oxygen evolution reaction with electrocatalysts is essential for efficient renewable-electricity-driven electrolysis. Active noble-metal catalysts suffer from leaching and scarcity, while non-noble alternatives face limited intrinsic activity. Here we combine computational guidance with experimental validation to identify atomically dispersed tungsten within NiFe oxyhydroxide, namely W<sub>1</sub>-NiFeOOH, as a promising noble-metal-free oxygen evolution reaction catalyst. An equivariant transformer-based machine-learning interatomic potential accelerates out-of-domain adsorption energy predictions and nominates W<sub>1</sub>-NiFeOOH from 3,976 single-atom-incorporated metal oxyhydroxide configurations. Cyclic-electrodeposited W<sub>1</sub>-NiFeOOH achieves a high current density of 13.1 A cm<sup>-2</sup> at 2.0 V and remains stable for 500 hours in alkaline exchange-membrane water electrolysis with commercial membranes. In situ spectroscopy and density functional theory calculations suggest that subsurface W promoter induces synergistic electron redistribution at neighboring Ni-O-Fe edge active sites, thereby lowering the proton-coupled electron-transfer barrier for the deprotonation step and facilitating transformation into the active γ-phase. This integrated computational-experimental workflow provides a blueprint for cost-effective catalyst design for sustainable energy systems.</p>

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Machine-learning-guided tungsten single atoms promote oxyhydroxides for noble-metal-free water electrolysis

  • Jaehyun Kim,
  • Ik Seon Kwon,
  • Jiheon Lim,
  • Sol A Lee,
  • Woo Seok Cheon,
  • Jin Hyuk Cho,
  • Sung Hyuk Park,
  • Yeong Jae Kim,
  • Mi Gyoung Lee,
  • Ki Chang Kwon,
  • Sun Hwa Park,
  • Soo Young Kim,
  • Ho Won Jang

摘要

Lowering the overpotential of oxygen evolution reaction with electrocatalysts is essential for efficient renewable-electricity-driven electrolysis. Active noble-metal catalysts suffer from leaching and scarcity, while non-noble alternatives face limited intrinsic activity. Here we combine computational guidance with experimental validation to identify atomically dispersed tungsten within NiFe oxyhydroxide, namely W1-NiFeOOH, as a promising noble-metal-free oxygen evolution reaction catalyst. An equivariant transformer-based machine-learning interatomic potential accelerates out-of-domain adsorption energy predictions and nominates W1-NiFeOOH from 3,976 single-atom-incorporated metal oxyhydroxide configurations. Cyclic-electrodeposited W1-NiFeOOH achieves a high current density of 13.1 A cm-2 at 2.0 V and remains stable for 500 hours in alkaline exchange-membrane water electrolysis with commercial membranes. In situ spectroscopy and density functional theory calculations suggest that subsurface W promoter induces synergistic electron redistribution at neighboring Ni-O-Fe edge active sites, thereby lowering the proton-coupled electron-transfer barrier for the deprotonation step and facilitating transformation into the active γ-phase. This integrated computational-experimental workflow provides a blueprint for cost-effective catalyst design for sustainable energy systems.