Facet-dependent structure and dissociation of water at pristine IrO<sub>2</sub>/water interfaces
ORAL
Abstract
Understanding the microscopic structure of water at metal oxide interfaces is crucial for advancing electrocatalysis. IrO2, in particular, has demonstrated exceptional activity for the electrochemical water oxidation, but we currently lack a fundamental understanding of how the surface structure of IrO2 impacts water reactivity. In this study, we developed a
machine learning potential trained to first principles accuracy for modeling IrO2/water interfaces across different facets: (110), (100), (101), and (001). Using extensive machine learning molecular dynamics simulations, we investigated the spontaneous dissociation of water molecules at these interfaces. Our results reveal a distinct dissociation probability
trend: (110) > (100) ≈ (101) > (001), which we attribute primarily to the reaction thermodynamics of surface water dissociation. A strong correlation is observed between the surface Ir-O bond distances and the dissociation probabilities, highlighting the role of surface geometry in modulating reactivity. As a consequence, the interfacial solvation structures and hydrogen bonding environments are dynamically tuned by the varying water dissociation capabilities across facets. This work elucidates how water dissociation energetics depend on surface orientation and the interfacial structure, offering atomistic insights for manipulating reaction chemistry at electrocatalytic interfaces.
machine learning potential trained to first principles accuracy for modeling IrO2/water interfaces across different facets: (110), (100), (101), and (001). Using extensive machine learning molecular dynamics simulations, we investigated the spontaneous dissociation of water molecules at these interfaces. Our results reveal a distinct dissociation probability
trend: (110) > (100) ≈ (101) > (001), which we attribute primarily to the reaction thermodynamics of surface water dissociation. A strong correlation is observed between the surface Ir-O bond distances and the dissociation probabilities, highlighting the role of surface geometry in modulating reactivity. As a consequence, the interfacial solvation structures and hydrogen bonding environments are dynamically tuned by the varying water dissociation capabilities across facets. This work elucidates how water dissociation energetics depend on surface orientation and the interfacial structure, offering atomistic insights for manipulating reaction chemistry at electrocatalytic interfaces.
*The work at Lawrence Livermore National Laboratory was performed under the auspices of the U.S. Department of Energy under Contract DE-AC52-07NA27344. Computational support is from the LLNL Grand Challenge Program. Work done at LLNL is supported by the HydroGEN Advanced Water Splitting Materials Consortium, established as part of the Energy Materials Network under the US Department of Energy, Office of Energy Efficiency and Renewable Energy, Hydrogen and Fuel Cell Technologies Office. MCA acknowledges the start-up funds provided by UCSC.
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Publication: J. Chem. Phys. in revision
Presenters
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Feiteng Wang
- University of California, Santa Cruz