Aqueous zinc-ion secondary batteries (AZIBs) have emerged as a leading candidate for next-generation energy storage due to their high safety, low cost, and environmental compatibility. Despite these advantages, challenges such as zinc dendrite formation, hydrogen evolution reaction (HER), cathode dissolution, and sluggish ion kinetics hinder their widespread commercialization. Theoretical computational studies have become indispensable in addressing these issues by providing atomic-level insights into reaction mechanisms, material properties, and interfacial behaviors. This comprehensive review systematically examines the role of computational methods, including density functional theory (DFT), molecular dynamics (MD), finite element method, machine learning (ML), and multiscale modeling, in advancing AZIBs research. We discuss their applications in cathode material design, anode stabilization, electrolyte optimization, and interfacial engineering. Additionally, we highlight the integration of computational predictions with experimental validations and outline future directions for accelerating AZIBs development.




