Suppressing dendrites in lithium metal anodes: A review of passivation layers and multiscale computational approaches

Lithium metal batteries (LMBs) have shown significant interest as next-generation energy storage systems due to their ultra-high theoretical specific capacity of 3,860 mAh g −1 . However, dendrite growth remains a major obstacle to commercialization, driven by instabilities in the native passivation layer (NPL) and the solid electrolyte interphase (SEI). The NPL, formed by lithium’s reactivity with ambient gases, induces uneven current distributions, while fragile SEIs crack easily, exposing fresh lithium and triggering parasitic reactions. This review combines experimental and computational approaches to understand and improve these interfacial layers. For the NPL, mechanothermal milling, picosecond laser treatments, vacuum thermal evaporation, and engineered electrodeposition layers have been employed to smooth surfaces and lower resistance. For the SEI, approaches such as artificial SEIs, electrolyte additives, solid-state electrolytes (SSEs), anode modification, and separator engineering enhance stability and suppress dendrite growth. Complementarily, computational methods including density functional theory (DFT), molecular dynamics (MD), ab initio molecular dynamics (AIMD), kinetic Monte Carlo (KMC), and machine learning (ML) provide atomistic insights into interfacial reactions and ion transport. Together, these experimental and computational approaches provide a unified framework that guides the design of stable interfacial layers and accelerates the safe commercialization of high-energy LMBs.