A Perspective on Multiscale Modeling of Explicit Solvation-Enabled Simulations of Catalysis at Liquid–Solid Interfaces
Ricardo A. García Cárcamo, Jiexin Shi, Ali Estejab, Tianjun Xie, Sanchari Bhattacharjee, Sayani Biswas, Cameron J. Bodenschatz, Xiuting Chen, Manish Maurya, Xiaohong Zhang, Rachel B. Getman
Abstract
Catalysis at liquid–solid interfaces is profoundly influenced by the interfacial solvent structure, which affects catalytic activity, selectivity, and reaction pathways. This perspective discusses state-of-the-art multiscale modeling methods that integrate quantum mechanics and molecular mechanics approaches to apply explicit solvent molecules to capture these interfacial phenomena. Specifically, the construction of multiscale models, the importance of capturing the interfacial solvent structure, and the computational strategies used to achieve this are explored, and the challenges in balancing chemical accuracy with computational expense are highlighted. Additionally, this perspective addresses the limitations of current methods. Opportunities for integrating machine learning are proposed. By advancing the efficiency and user friendliness of multiscale modeling, it is argued that deeper insights into heterogeneous catalysis in the liquid phase can be provided, which will ultimately contribute to the development of more efficient catalytic processes.