Molecular Modelling of Aqueous Batteries

Aqueous batteries play an increasingly important role in the development of sustainable and safety-prioritized energy storage solutions. Compared to conventional lithium-ion batteries, the cell chemistry in aqueous batteries shares many common features with those of electrolyzer and pseudo-capacitor systems because of the involvement of aqueous electrolytes and proton activity. This imposes the need for a better understanding of the corresponding ion solvation, intercalation, and electron transfer processes at an atomic scale. Therefore, this chapter provides an up-to-date overview of molecular modelling techniques and their applications in aqueous batteries. In particular, we emphasize the dynamical and reactive description of aqueous battery systems brought in by density functional theory-based molecular dynamics simulation (DFTMD) and its machine-learning (ML) accelerated counterpart. Moreover, we also cover the recent advancement of generative artificial intelligence (AI) in molecular and materials design of aqueous batteries. Case studies presented here include popular aqueous battery systems, such as water-in-salt electrolytes, proton-coupled cathode materials, Zn-ion batteries, and organic redox flow batteries.