Chemo-mechanical modeling of defective graphene for energy storage in Lithium-Ion Battery

The process of Li insertion and extraction imparts repeated mechanical loading and unloading of anode materials which ultimately leads to mechanical degradation and battery failure. With the persistent need to model efficient anode materials that can withstand repeated mechanical loading, we have looked into the potential of defective graphene(DG) based 2D materials which have enhanced Li adsorption and good mechanical strength to undergo several cycles of charge-discharge. In this work, we have primarily used grand canonical Monte Carlo and molecular dynamics (GCMC-MD hybrid) to model complete charge and discharge profiles of DG varying from single layer to multilayered systems. Stress distribution upon charge and discharging have been analyzed to predict crack nucleation and propagation. Density Functional Theory (DFT) was used to benchmark our GCMC-MD results. Enhanced adsorption of Li resulted in incomplete desorption during discharging which resulted in decreased over-all charge-discharge cycle stability of the system. Further, inherently having low shear strength, it was determined that the presence of Li atoms significantly affects the overall slippage of one DG over another along with their load-bearing capacity.