Continuum-Level Modeling of Li-Ion Battery SEI by Upscaling Atomistically Informed Reaction Mechanisms

Peter Weddle, Evan Spotte-Smith, Ankit Verma, Hetal Patel, Kae Fink, Bertrand Tremolet de Villers, Maxwell Schulze, Samuel Blau, Kandler Smith, Kristin Persson, Andrew Colclasure

Research output: Contribution to journalArticlepeer-review


Understanding and controlling solid-electrolyte interphase (SEI) formation to stabilize cell performance is a significant challenge for next-generation Li-ion battery technologies. In recent years, computational modeling has become an essential tool in providing fundamental insights into SEI properties and dynamics. However, neither atomistic nor continuum-level approaches alone can capture the complexities of SEI chemistry across all relevant length and time scales. In this work, a continuum-level model is developed that is informed by reaction mechanisms obtained from first-principle calculations. The atomistically informed continuum-level model is used to understand electrolyte degradation, including the decomposition of ethylene carbonate (EC), ethyl methyl carbonate (EMC), and fluoroethylene carbonate (FEC). The model presented here is the most chemically complex continuum-level SEI model in the literature to date. The SEI model is calibrated against experimental irreversible leakage currents and shows qualitative agreement with expected SEI growth trends. The model framework is expected to accelerate fundamental understanding of SEI formation, facilitate mechanism development feedback, and dynamically interact with experimental insights.

Original languageAmerican English
Article number143121
Number of pages20
JournalElectrochimica Acta
StatePublished - 2023

Bibliographical note

Publisher Copyright:
© 2023 Elsevier Ltd

NREL Publication Number

  • NREL/JA-5700-86293


  • Continuum-level model
  • Lithium-ion battery
  • Silicon anode
  • Solid-electrolyte interphase


Dive into the research topics of 'Continuum-Level Modeling of Li-Ion Battery SEI by Upscaling Atomistically Informed Reaction Mechanisms'. Together they form a unique fingerprint.

Cite this