Towards Real-Time Simulation of Two-Dimensional Models for Electrodeposition/Stripping in Lithium-Metal Batteries

Abstract

Lithium metal anode has been tipped to be the most likely successor of graphite anode in the next generation lithium-based batteries. However, this has not been translated into commercialized lithium metal batteries. While there has been remarkable progress in the experimental design of lithium metal batteries with improved performance1-3, there is limited work on accurate models and robust simulation to study microstructure evolution in lithium metal anode. There also lacks a modeling framework that relates morphological changes with corresponding system-level response in a simultaneous manner. Such a framework can prove to be key in designing lithium metal batteries with long life and high performance. The challenges in developing the same has been discussed in our perspective article4. We also recently reported a simple 1D model to study plating and stripping in lithium metal anode5.In this work, a simple 2D geometry is considered to formulate the model equations and analyze the numerical challenges in (1) spatial discretization, (2) time evolution of the moving boundary to capture deposition/stripping, and (3) optimal discretization scheme in time. A detailed analysis will be presented to compare the standard finite difference/finite element methods and hybrid in-house schemes optimized for the electrochemical model based on coordinate transformation and combination of different numerical schemes. Cycling simulations are performed under different operating conditions considering various cases with surface inhomogeneities, singularity, and initial lithium nuclei.Depending on the geometric, kinetic, and transport parameters, the growth rate and shape of the lithium deposit varies, which in turn affect the cyclability and rate capability of the battery. Our proposed model for predicting metal deposition and stripping in lithium metal batteries brings together the mesoscale and electrochemical models and can pave the path towards achieving tailored morphological characteristics to make lithium metal anodes viable in commercial systems. In this talk, we will present results on computational efficiency and numerical accuracy of different formulations and spatial and temporal discretization methods. We will also discuss the real-time simulation of the proposed model for deriving optimal charging profiles. Acknowledgments This research was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies of the US Department of Energy (DoE) through the Advanced Battery Materials Research Program (Battery500 Consortium). References K. N. Wood, E. Kazyak, A. F. Chadwick, K. H. Chen, J. G. Zhang, K. Thornton, and N. P. Dasgupta, ACS Cent. Sci., 2, 790-801 (2016).J. Liu, Z. Bao, Y. Cui, E. Dufek, J. B. Goodenough, P. Khalifah, Q. Li, B. Liaw, P. Liu, A. Manthiram, Y. S. Meng, V. R. Subramanian, M. F. Toney, V. V. Viswanathan, M. S. Whittingham, J. Xiao, W. Xu, J. Yang, X. Yang, and J. Zhang, Nat. Nanotechnol., 14 180-186 (2019).A. Pei, G. Zheng, F. Shi, Y. Li, and Y. Cui., Nano Lett., 17(2), 1132-1139 (2017).K. Shah, A. Subramaniam, L. Mishra, T. Jang, M. Z. Bazant, R. D. Braatz, and V. R. Subramanian, J. Electrochem. Soc., 167, 133501 (2020).M. Uppaluri, A. Subramaniam, L. Mishra, V. Viswanathan, and V. R. Subramanian, J. Electrochem. Soc., 167, 160547 (2020).T. Jang, L. Mishra, K. Shah, P. Mittal, A. Subramaniam, M. P. Gururajan, S. A. Roberts, and V. R. Subramanian, 2021 ECS Meet. Abstr. (239th Meeting, in progress)