Machine-Learning-Accelerated Surface Exploration of Reconstructed BiVO$_{4}$(010) and Characterization of Their Aqueous Interfaces

TL;DR

This study employs advanced machine learning and computational techniques to explore and characterize complex reconstructed BiVO$_{4}$(010) surfaces, revealing spontaneous water dissociation and providing insights into PEC interface reactivity.

Contribution

It introduces a novel computational workflow combining active learning, global optimization, and hybrid functional simulations to identify and analyze reconstructed BiVO$_{4}$(010) surfaces and their reactivity.

Findings

Identified 494 unique reconstructed surface structures surpassing traditional models.

Proposed structural models for Bi-rich BiVO$_{4}$ surfaces under experimental conditions.

First theoretical report of spontaneous water dissociation on reconstructed BiVO$_{4}$(010) surfaces.

Abstract

Understanding the semiconductor-electrolyte interface in photoelectrochemical (PEC) systems is crucial for optimizing stability and reactivity. Despite the challenges in establishing reliable surface structure models during PEC cycles, this study explores the complex surface reconstructions of BiVO$_{4}$(010) by employing a computational workflow integrated with a state-of-the-art active learning protocol for a machine-learning interatomic potential and global optimization techniques. Within this workflow, we identified 494 unique reconstructed surface structures that surpass conventional chemical intuition-driven, bulk-truncated models. After constructing the surface Pourbaix diagram under Bi- and V-rich electrolyte conditions using density functional theory and hybrid functional calculations, we proposed structural models for the experimentally observed Bi-rich BiVO$_{4}$ surfaces. By performing hybrid functional molecular dynamics simulations with explicit treatment of water molecules on selected reconstructed BiVO$_{4}$(010) surfaces, we observed spontaneous water dissociation, marking the first theoretical report of this phenomenon. Our findings demonstrate significant water dissociation on reconstructed Bi-rich surfaces, highlighting the critical role of bare and under-coordinated Bi sites (only observable in reconstructed surfaces) in driving hydration processes. Our work establishes a foundation for understanding the role of complex, reconstructed Bi surfaces in surface hydration and reactivity. Additionally, our theoretical framework for exploring surface structures and predicting reactivity in multicomponent oxides offers a precise approach to describing complex surface and interface processes in PEC systems.