Unveiling the Electrocatalytic Hydrogen Evolution Reaction Pathway on RuP<sub>2</sub> through Ab Initio Grand Canonical Monte Carlo

In this study, the high catalytic reactivity of ruthenium phosphide (RuP2) has been identified by first-principles density functional theory (DFT) calculations for the electrocatalytic hydrogen evolution reaction (HER). Complex surface reconstructions are considered by applying the ab initio grand canonical Monte Carlo (ai-GCMC) algorithm, efficiently providing a sufficient phase-space exploration of possible surfaces. Combined with surface-phase Pourbaix diagrams, we are able to identify the actual surfaces that obtained under specific experimental environments, thus leading to a more accurate understanding of the nature of the active sites and the binding strength of adsorbates. Specifically, through hundreds of surface reconstructions and hydrogenation states generated with ai-GCMC, we identify the most favorable surface phases of RuP2 under aqueous acidic conditions. We discover that the HER activity is determined by multiple surfaces with different stoichiometries within a narrow electrode potential window. Low HER overpotential (η) has been found for each of the identified surfaces, as low as 0.04 V. High H-coverage reconstructed surfaces have been discovered under acidic conditions, and the surface Ru sites introduced by additional Ru adatoms or exposed by P-vacancies serve as the active sites for HER based on their nearly reversible H binding. This work provides atomistic insights into the origin of high HER activity on RuP2 by exploring the dynamic surface phases of electrocatalysts and features a generalizable method to explore the reconstructed/hydrogenated surface space as a function of experimental conditions.

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Publication Details

Journal
ACS Catalysis
Published
2024-11-08
DOI
https://doi.org/10.1021/acscatal.4c04913
Citations
6
Primary Topic
Electrocatalysts for Energy Conversion
Type
article
Field-Weighted Citation Impact
0.61

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article

Unveiling the Electrocatalytic Hydrogen Evolution Reaction Pathway on RuP2 through Ab Initio Grand Canonical Monte Carlo

Shihan Qin, Andrew M. Rappe, Sayan Banerjee, Mehmet Gökhan Şensoy
6 citations
ACS Catalysis
Electrocatalysts for Energy Conversion
0.61
article

Unveiling the Electrocatalytic Hydrogen Evolution Reaction Pathway on RuP2 through Ab Initio Grand Canonical Monte Carlo

Shihan Qin, Andrew M. Rappe, Sayan Banerjee, Mehmet Gökhan Şensoy
article en
6 citations

Abstract

In this study, the high catalytic reactivity of ruthenium phosphide (RuP2) has been identified by first-principles density functional theory (DFT) calculations for the electrocatalytic hydrogen evolution reaction (HER). Complex surface reconstructions are considered by applying the ab initio grand canonical Monte Carlo (ai-GCMC) algorithm, efficiently providing a sufficient phase-space exploration of possible surfaces. Combined with surface-phase Pourbaix diagrams, we are able to identify the actual surfaces that obtained under specific experimental environments, thus leading to a more accurate understanding of the nature of the active sites and the binding strength of adsorbates. Specifically, through hundreds of surface reconstructions and hydrogenation states generated with ai-GCMC, we identify the most favorable surface phases of RuP2 under aqueous acidic conditions. We discover that the HER activity is determined by multiple surfaces with different stoichiometries within a narrow electrode potential window. Low HER overpotential (η) has been found for each of the identified surfaces, as low as 0.04 V. High H-coverage reconstructed surfaces have been discovered under acidic conditions, and the surface Ru sites introduced by additional Ru adatoms or exposed by P-vacancies serve as the active sites for HER based on their nearly reversible H binding. This work provides atomistic insights into the origin of high HER activity on RuP2 by exploring the dynamic surface phases of electrocatalysts and features a generalizable method to explore the reconstructed/hydrogenated surface space as a function of experimental conditions.

ACS CatalysisVol. 14(23)
University of Pennsylvania (US)
National Science Foundation, Basic Energy Sciences
Openalex Percentile: Top 39%
Electrocatalysts for Energy Conversion
0.61
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