Interactive multiscale modeling to bridge atomic properties and electrochemical performance in Li-CO2 battery design

Li-CO₂ batteries are promising energy storage systems due to their high theoretical energy density and CO₂ fixation capability, relying on reversible Li₂CO₃/C formation during discharge/charge cycles. We present a multiscale modeling framework integrating Density Functional Theory (DFT), Ab-Initio Molecular Dynamics (AIMD), classical Molecular Dynamics (MD), and Finite Element Analysis (FEA) to investigate atomic and cell-level properties. The considered Li-CO₂ battery consists of a lithium metal anode, an ionic liquid electrolyte, and a carbon cloth cathode with Sb_0.67Bi_1.33Te₃ catalyst. DFT and AIMD determined the electrical conductivities of Sb_0.67Bi_1.33Te₃ and Li₂CO₃ using the Kubo–Greenwood formalism and studied the CO₂ reduction mechanism on the cathode catalyst. MD simulations calculated the CO₂ diffusion coefficient, Li${}^{+}$ transference number, ionic conductivity, and Li${}^{+}$ solvation structure. The FEA model, parameterized with atomistic simulation data, reproduced the available experimental voltage–capacity profile at 1 mA/cm² and revealed spatio-temporal variations in Li₂CO₃/C deposition, porosity, and CO₂ concentration dependence on discharge rates in the cathode. Accordingly, Li₂CO₃ can form large and thin film deposits, leading to dispersed and local porosity changes at 0.1 mA/cm² and 1 mA/cm², respectively. The capacity decreases exponentially from 81,570 mAh/g at 0.1 mA/cm² to 6200 mAh/g at 1 mA/cm², due to pore clogging from excessive discharge product deposition that limits CO₂ transport to the cathode interior. Therefore, the performance of Li-CO₂ batteries can be improved by enhancing CO₂ transport, regulating Li₂CO₃ deposition, and optimizing cathode architecture.