Interactive Multiscale Modeling to Bridge Atomic Properties and Electrochemical Performance in Li-CO2 Battery Design
Abstract
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 simulations 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 6,200 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.
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