Synergism between metal single-atom sites and S-vacant two-dimensional nanosheets for efficient hydrogen evolution uncovered by density functional theory and machine learning

Abstract

Efficient electrocatalysts for the hydrogen evolution reaction (HER) are the key to hydrogen-electricity energy conversion. Leveraging density functional theory and machine learning, we herein reveal the synergism between metal single atoms (M-SAs) and S-vacant two-dimensional (2D) MnPS₃ nanosheets (S_v-MnPS₃). Specifically, M-SAs occupy S-vacancies and activate the neighboring S sites as new active sites for the HER. In turn, S_v-MnPS₃ improves the ability of metal-SAs for water dissociation by modulating their magnetic moments. During the HER, H* is generated on metal-SAs and then migrates to neighboring S sites on which H₂ is produced, representing catalytic synergism via hydrogen spillover. Among the M₁/S_v-MnPS₃ candidates, Pd₁/S_v-MnPS₃ possesses an optimal ΔG_H* of 0.01 eV and is both thermodynamically and electrochemically stable. Therefore, the synergism between Pd₁ and S_v-MnPS₃ enables Pd₁/S_v-MnPS₃ to be active and durable for the HER. This work provides insights into how to design and understand confined metal-SAs in 2D materials for efficient electrocatalysis.