Abstract:

The functioning of Li metal-solid state batteries (LMSSB) requires that interfacial contact between the Li metal anode and the solid electrolyte (SE) be maintained during cycling. A reduction in contact area during Li stripping will increase the local current density during subsequent Li plating, fostering dendrite nucleation. The contact area is influenced by the rate of Li transport within the anode towards the interface. Relevant transport mechanisms include diffusion and creep, with faster rates of these processes resulting in improved performance. Given the importance of these transport modes, predicting them as a function of the anode's microstructure, stress state, and temperature will be helpful in the design of LMSSB. Here, the rates of diffusion and creep in Li are predicted using atomic scale simulations. A primary goal is to understand if and how Li microstructure impacts the performance of LMSSB. First, molecular dynamics is used to estimate the rate of Li diffusion along dislocations and in grain boundary triple junctions. By combining this data with that from a prior study of grain boundary diffusion, the dominant diffusion mechanisms and overall rates of self-diffusion in Li polycrystals are predicted as a function of grain size, grain shape, dislocation density, and temperature. A 1D continuum model for interfacial contact is parameterized using the computed diffusion data. The model predicts that high dislocation densities (~10 12 /cm 2 ) and/or small grain sizes (~10 m) enable achieving battery performance targets. Secondly, the dominant creep deformation mechanisms are predicted as a function of applied stress, grain size, and temperature. Grain boundary sliding and coble creep are observed to be the primary mechanisms for micron-sized grains. Finally, a kinetic lattice Monte Carlo model is developed to monitor the dynamics of Li voids as a function of interfacial thermodynamics and the presenceof grain boundaries.

Bio:

Don Siegel is Professor and Chair of the Walker Department of Mechanical Engineering at the University of Texas at Austin. He also has appointments in the Oden Institute for Computational Engineering and Sciences and the Texas Materials Institute. At UT he is a Temple Foundation Endowed Professor and holds a Cockrell Family Chair for Departmental Leadership. Prior to joining UT in 2021, Prof. Siegel spent 12 years at the University of Michigan, with earlier posts in industry (Ford Motor Company) and at national laboratories (Sandia National Lab and the U.S. Naval Research Lab). Siegel is a computational materials scientist whose research targets the development of energy storage materials and lightweight alloys. He is a recipient of the NSF Career Award and a Gilbreth Lectureship from the National Academy of Engineering.