(461h) A Comprehensive Investigation of Dendrite Formation in Lithium Anode Batteries: A Computational Approach for Heterogenous SEI | AIChE

(461h) A Comprehensive Investigation of Dendrite Formation in Lithium Anode Batteries: A Computational Approach for Heterogenous SEI


Sitapure, N. - Presenter, Texas A&M University
Kwon, J., Texas A&M University
Balbuena, P., Texas A&M University
Lee, H., Texas A&M University
Hwang, S., Inha University
Lithium-ion batteries (LIB) are ubiquitously used as energy storage devices in electronics, communication, electric vehicles, etc. Most of the LIB employ a graphite anode, which unfortunately has a low energy density of ~ 372 mAh/g1. There are growing appeals for Li metal being the ‘Holy-Grail’ anode in LIB due to its high energy density (~ 3862 mAh/g). However, it is plagued by uncontrollable and unpredictable dendrite growth resulting in poor cycling efficiency, and in extreme cases, short-circuiting of batteries. The literature is rife with studies highlighting different factors that aid/cause dendrite formation, viz., overpotential, temperature2, number of charge-discharge cycles, etc. However, there are very few studies addressing the complex interaction between heterogenous solid-electrolyte interface (SEI) and the growing dendrite. Hence, a detailed mechanistic study of factors affecting dendrite growth and the complicated SEI-dendrite interactions, which can help in devising mitigation strategies, is highly coveted in the materials community.

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 Young’s 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 Young’s 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

  1. Cheng, X.-B., Zhang, R., Zhao, C.-Z. & Zhang, Q. Toward safe lithium metal anode in rechargeable batteries: a review. Chemical reviews 117, 10403–10473 (2017).
  2. Hao, F., Verma, A. & Mukherjee, P. P. Mechanistic insight into dendrite–SEI interactions for lithium metal electrodes. Journal of Materials Chemistry A 6, 19664–19671 (2018).
  3. Qin, X., Shao, M. & Balbuena, P. B. Elucidating mechanisms of Li plating on Li anodes of lithium-based batteries. Electrochimica Acta 284, 485–494 (2018).
  4. Mehdi, B. L. et al. Observation and quantification of nanoscale processes in lithium batteries by operando electrochemical (S) TEM. Nano letters 15, 2168–2173 (2015).
  5. Wood, K. N. et al. Dendrites and pits: Untangling the complex behavior of lithium metal anodes through operando video microscopy. ACS central science 2, 790–801 (2016).