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 Sb0.67Bi1.33Te3 catalyst. DFT and AIMD determined the electrical conductivities of Sb0.67Bi1.33Te3 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.