  Aqueous batteries play an increasingly important role for the development of
sustainable and safety-prioritised energy storage solutions. Compared to
conventional lithium-ion batteries, the cell chemistry in aqueous batteries
share many common features with those of electrolyzer and pseudo-capacitor
systems because of the involvement of aqueous electrolyte and proton activity.
This imposes the needs for a better understanding of the corresponding ion
solvation, intercalation and electron transfer processes at atomistic scale.
Therefore, this chapter provides an up-to-date overview of molecular modelling
techniques and their applications in aqueous batteries. In particular, we
emphasize on 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 as well as
organic redox flow batteries.
