Unraveling charge effects on interface reactions and dendrite growth in lithium metal anode

Li metal is acknowledged as an ultimate anode material for high-specific-energy batteries, although its safety and practical cyclability heavily depend on the mysterious interface between Li metal and liquid electrolyte (LLI). However, there are substantial gaps in understanding the multiple intertwined chemical and electrochemical processes occurring on the LLI. Here, we unprecedentedly present the disentangled analyses of these processes and correlate them with Li dendrite growth by multi-scale simulation techniques combining machine-learning-driven molecular dynamics and phase-field modeling. Our simulations demonstrate a close relationship between Li dendrite growth and the interface reactions, which can be attributed to the charge transfer process. We further reveal that the behaviors of bond cleavages can be regulated by varying charge distribution at the interface. We propose that the charge transfer kinetics, revealed by the newly developed formulism of machine learning potential incorporating charge information, can act as a descriptor to explain the driving forces behind these behaviors on the LLI. This work enables new opportunities to fundamentally understand the intertwined processes occurring on the LLI and provide crucial new insights into the electrode-electrolyte interface design for next-generation high-specific-energy batteries.