(461h) A Comprehensive Investigation of Dendrite Formation in Lithium Anode Batteries: A Computational Approach for Heterogenous SEI
AIChE Annual Meeting
2020
2020 Virtual AIChE Annual Meeting
Computing and Systems Technology Division
Applied Math for Energy and Environmental Applications
Wednesday, November 18, 2020 - 9:45am to 10:00am
The focus of this work is to address the above-mentioned knowledge gap by proposing a first-principled mesoscopic kinetic Monte Carlo (KMC) simulation in combination with DFT studies to simulate dendrite growth in LIB. The KMC employs fundamental events, viz., Li+ desolvation, diffusion of Li+ in the solid SEI, and Li reduction. The desolvation rate, , accounts for the effect of different electrolytes. The Li+ diffusion rate, , changes with different SEI species, viz., Li2O, LiF, RoLi, etc. The Li+ reduction rate accounts for the effect of overpotential and process temperature. The microscopic events are modelled based on known and/or new DFT studies2,3. Furthermore, the simulations account for the spatio-temporal evolution of the heterogenous SEI due to dendrite formation. The SEI evolution is predicted based upon the ratio of Youngâs moduli of different SEI species.
The KMC simulation predicts accelerated dendrite formation for the case of a realistic heterogenous SEI as compared to an ideal homogenous SEI case, showcasing the effect of heterogenous SEI. To illustrate this observation, video snapshots of the simulations were generated showing the temporal evolution of Li depositions into mossy, tree-like dendrites, which are consistent with experimental results4. However, at elevated temperatures and low overpotential values, the Li deposition was more uniform, even for a heterogenous SEI. The effect of SEI-dendrite interaction was evident from the simulation results which showed that softer SEI species (low Youngâs modulus) viz., ROLi, ROCO2Li, underwent more SEI displacement as compared to rigid SEI species viz., LiF, Li2O. Furthermore, DFT calculations were performed for the fast-screening of potential electrolytes which are suitable for mitigation of dendrite growth3.
In summary, the work provides a comprehensive computational analysis of various factors affecting dendrite growth in a realistic heterogenous SEI environment and underlines the importance of physical and chemical interaction between the SEI and dendrites. The combination of DFT and KMC highlights the value of multiscale modelling in the formulation of mitigation strategies for dendrite formation in LIB.
Literature Cited
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