Species Distribution During Solid Electrolyte Interphase Formation on Lithium Using MD/DFT-Parameterized Kinetic Monte Carlo Simulations

Abstract

Lithium metal batteries are one of the promising technologies for future energy storage. One open challenge is the generation of a stable and well performing Solid Electrolyte Interphase (SEI) between lithium metal and electrolyte. Understanding the complex interaction of reactions at the lithium surface and the resulting SEI is crucial for knowledge-driven improvement of the SEI. This study reveals the internal species distribution and geometrical aspects of the native SEI during formation by model-based analysis. To achieve this, a combination of molecular dynamics, density functional theory, and stand-alone 3D-kinetic Monte Carlo simulations is used. The kinetic Monte Carlo model determines the SEI growth features over a long time and length scale so that the SEI can be analyzed quantitatively. The simulation confirms the frequently postulated layered SEI structure arising from the decomposition of an ethylene carbonate/lithium hexafluorophosphate (2 M) electrolyte with lithium metal. These layers are not clearly separated, which is contrary to what is often reported. The gradient distribution of the species within the SEI therefore corresponds to a partly mosaic structured SEI at the borders of the layers. At the lithium surface, an inorganic layer of lithium fluoride and then lithium carbonate is observed, followed by an organic, more porous SEI layer consisting of lithium ethylene dicarbonate. Simulations further reveal the strong prevalence of corrosion processes of the metal, which provide more than 99% of the lithium for the SEI reaction processes. The salt contributes less than 1% to the SEI formation. Additionally, SEI formation below and above the initial interface was observable. The here presented novel modeling approach allows an unprecedented in-depth analysis of processes during native SEI formation that can be used to improve design for high battery performance and durability.

Multiscale Investigation of Sodium‐Ion Battery Anodes: Analytical Techniques and Applications

“…Recently, a kMC model has been developed to examine SEI growth in Li‐metal systems at a level of detail far beyond prior studies. [ 328 ] In this work, electrolyte reaction pathways and barriers were supplied from DFT calculations, and the Li metal/electrolyte interface was simulated at open circuit conditions. The model accurately simulated the growth of the SEI layer and provided novel insights about the composition and distribution of species.…”

Atomistic Scale Modeling of Anode/Electrolyte Interfaces in Li-Ion Batteries

“…Recently, the hybrid continuum models combined with DFT, MD, and kinetic Monte Carlo (kMC) have attracted interest owing to their capacity to simulate longer time scales with larger systems compared to the current DFT and MD simulations, facilitating the understanding of the dynamic evolving nature of the SEI layer. For example, Gerasimov et al recently studied the SEI formation and growth on the Li metal anode using a combination of MD/DFT and 3D-kMC simulations and successfully analyzed the dynamic evolution processes of SEI . Furthermore, deep potential molecular dynamics (DeePMD), based on the deep neural network trained ab initio data, has also received considerable interest in the modeling of multistructured SEI as it helps to overcome the limitations in the time and length scale of AIMD simulations, while maintaining a high level of accuracy .…”

Lithium-ion battery cell formation: status and future directions towards a knowledge-based process design

“…Due to the changing conditions and the different reactants and intermediates, several reactions compete during the initial formation, resulting in a heterogeneous structure, which was first introduced by Peled et al 488,489 To obtain spatially resolved insights on the SEI structure, first-principle simulations and the kinetic Monte Carlo (kMC) method were used. 306,454,[490][491][492][493][494][495][496] Although first-principle studies provide spatially resolved information on the SEI and have made progress on the time scale, 497 they are still limited to the ns range and are therefore unable to describe complete formation cycles. Compared to ab initio simulations, kMC allows longer time scales to be simulated while preserving atomistic detail.…”