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<p>Solid–liquid interfaces, especially those involving water and aqueous solutions, play a prominent role in contemporary environmental and energy applications. Chemical reactions at these interfaces ranging from geochemical processes to electrocatalysis are impacted by the local interface structure and its dynamic evolution, which poses a significant challenge to both experimental and computational approaches in providing an accurate molecular-level characterization under operating conditions. This review summarizes the computational modeling efforts starting from first-principles based methods to state-of-the-art simulations using machine-learning potentials that have been at the forefront in advancing our understanding of these complex systems. A road map for the future is also provided by identifying the unresolved questions that persist.</p>

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Computational Modeling of Solid–Liquid Interfaces: From Ab Initio Methods to Machine-Learning Potentials

  • 期刊论文

  • 发表日期：

    2025年7月5日

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  • Abhinav S. Raman

摘要

Solid–liquid interfaces, especially those involving water and aqueous solutions, play a prominent role in contemporary environmental and energy applications. Chemical reactions at these interfaces ranging from geochemical processes to electrocatalysis are impacted by the local interface structure and its dynamic evolution, which poses a significant challenge to both experimental and computational approaches in providing an accurate molecular-level characterization under operating conditions. This review summarizes the computational modeling efforts starting from first-principles based methods to state-of-the-art simulations using machine-learning potentials that have been at the forefront in advancing our understanding of these complex systems. A road map for the future is also provided by identifying the unresolved questions that persist.