Understanding interfacial evolution in solid-state batteries using machine learning force fields

POSTER

Abstract

The interfacial instabilities in solid-state batteries (SSBs) significantly affect the cell performance. In this talk, we will demonstrate direct observation of interfacial evolution at the Li7La3Zr2O12 (LLZO) solid-electrolyte/LiCoO2 cathode interface from large-scale molecular dynamic simulations enabled by validated machine-learning force fields (MLFFs). Our results unravel the relationship between the surface chemistries of LLZO and LCO and propensities for interfacial degradation. We will further address the impact of element doping (as often found in LLZO) on Li-ion transport in single grain LLZO and its grain boundaries (GBs). It is observed that dopants tend to segregate at the LLZO GBs and form clusters that can lead to prenucleation of dopant-rich secondary phases at the GBs. This phenomenon is presumed to be general regardless of the type of GBs. Our findings imply that interlayer design may be needed to alleviate the intrinsic interfacial degradation for enhanced performance.

* This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract number DEAC52-07NA27344. Authors acknowledge funding support from the Vehicle Technologies Office, Office of Energy Efficiency and Renewable Energy, U.S. Department of Energy and computational resource support from the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program.

Presenters

  • Kwangnam Kim

    Lawrence Livermore National Laboratory

Authors

  • Kwangnam Kim

    Lawrence Livermore National Laboratory

  • Suyue Yuan

    Lawrence Livermore National Laboratory

  • Aniruddha M Dive

    Lawrence Livermore National Laboratory

  • Andrew Grieder

    University of California, Santa Cruz

  • Nicole Adelstein

    San Francisco State University

  • ShinYoung Kang

    Lawrence Livermore Natl Lab

  • Brandon Wood

    Lawrence Livermore National Laboratory

  • Liwen Wan

    Lawrence Livermore National Laboratory