Reactivity and structure evolution of B-rich metal diboride surface in acidic electroreduction conditions
ORAL
Abstract
Boron is an element known for rich polymorphic forms and multi-center bonding modes. Even in metal borides, the boron content still has a great diversity of geometric and electronic structures and dictates the reactivity towards multiple catalytic reactions. In this work, we study the hexagonal face of MoB2 which has the highest activity towards hydrogen evolution reaction (HER) among all stoichiometric borides, by a combination of grand canonical global optimization and reaction path sampling. We show that, by filling the centers of some of the B6 hexagons with added B (possible via a simple boronizing treatment), the H adsorption energetics of the surface can be tuned.
More interestingly, upon H coverage, the center B becomes mobile and can hop among hexagons. Their thermodynamic fate is to form a global minimum trimer configuration that is HER-inactive, at more negative potentials, form borane that desorbs. Extensive reaction path samplings are then performed to determine the kinetic feasibility of those deactivation pathways, so as to construct a kinetically accessible sub-ensemble that is relevant to the HER condition. We are also training machine learning interatomic potential with the global optimization trajectories, aiming to simulate the system at larger size scales and longer time scales.
More interestingly, upon H coverage, the center B becomes mobile and can hop among hexagons. Their thermodynamic fate is to form a global minimum trimer configuration that is HER-inactive, at more negative potentials, form borane that desorbs. Extensive reaction path samplings are then performed to determine the kinetic feasibility of those deactivation pathways, so as to construct a kinetically accessible sub-ensemble that is relevant to the HER condition. We are also training machine learning interatomic potential with the global optimization trajectories, aiming to simulate the system at larger size scales and longer time scales.
*This computational research was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division, Catalysis Science Program to the SUNCAT Center for Interface Science and Catalysis. Z.Z. acknowledges the Stanford Energy Postdoctoral Fellowship from the Precourt Institute of Energy at the Doerr School of Sustainability at Stanford University.
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Presenters
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Zisheng Zhang
- Stanford University & SLAC