(Invited, Digital Presentation) Detailed Chemical Modeling of Solid Electrolyte Interphase Growth and Evolution

Abstract

The solid electrolyte interphase (SEI) is a layer that forms at the anode-electrolyte interphase in lithium ion batteries. The layer forms due to voltage instability of the electrolyte at low anode potentials, but serves to passivate the electrolyte to protect against further uncontrolled decomposition. In theory, the SEI is self-limiting, but in reality, continued growth over the battery’s lifetime leads to capacity fade, poor rate capability, and eventually cell death. Though significant progress in recent years has improved the SEI’s function and stability, poor understanding of its most basic chemistry impedes “rational design” of SEI layers for advanced battery applications. Understanding and quantifying the elementary chemistry of the SEI is made challenging by the layer’s thickness (10s to ~100 nm), chemical sensitivity, mechanical fragility, and complex chemistry (upwards of 100 reactions have been proposed). For these reasons, These factors combine to make studying the fundamental chemistry of SEI growth and evolution a significant challenge. Both the computational tools to model the SEI’s complex chemistry and the experimental data required to validate such models are all too rare.This talk will provide an overview of recent efforts to model the fundamental electrochemistry of SEI growth and evolution. The simulations are based on a continuum-scale, finite-volume framework, and leverage the open-source software package Cantera to enable efficient simulation of arbitrarily complex electrochemical mechanisms. Simulation results, as in Figure 1, are validated against two operando measurements of the SEI grown on a non-intercalating tungsten anode: depth profiling via neutron reflectometry (NR), and SEI mass uptake data via quartz crystal microbalance with dissipation (QCM-D) taken during cyclic voltammetry cycling. Interrogation of the detailed model results provide insights into the complex phenomena controlling initial SEI growth, and validation against NR and QCM-D data identify prominent reaction pathways and key chemical species present in the SEI. Finally, we will conclude by discussing future steps, includuing transferring mechanistic insights to new scales, geometries, and chemistries, and coupling models with inputs from atomistic simulations. Figure 1