Research Seminar - Evan Walter Clark Spotte-Smith

Predicting Solid Electrolyte Interphase Formation Mechanisms Via Reaction Networks and Microkinetic Modeling

Lithium-ion batteries (LIBs) are a staple energy storage technology, powering everything from personal phones to automobiles. LIBs have become technologically viable in large part due to the solid electrolyte interphase (SEI), a nanoscale passivation layer that forms from irreversible electrolyte reduction during initial battery charging. The SEI protects the electrode and prevents further electrolyte reduction. Understanding the chemistry of the SEI is therefore vital to improve battery lifespans and design next-generation energy storage technologies. However, it is notoriously difficult to characterize the SEI experimentally, and conventional theoretical methods can provide only limited insights due to their computational cost and reliance on chemical intuition. As a result of
these limitations, two fundamental questions remain unresolved: what products form in the SEI, and how do those products form?

In this seminar, Evan will present a new approach to explore such questions of electrochemical reactivity by leveraging chemical reaction networks (CRNs). They will describe general methods to generate and analyze massive CRNs containing tens of millions of reactions. Applying these methods to SEI formation, they automatically identify plausible SEI products and predict favorable formation pathways to key species of interest. Evan will also describe their recent work developing a microkinetic model of SEI formation and evolution. For the first time, this model recovers the bilayer Peled structure of the SEI entirely from first principles, and it can explain how this structure emerges as a result of reactive competition between different SEI products. By conducting simulations at elevated temperature, they develop an understanding of how SEI components can decompose over time, leading to a continual evolution of the interphase. These findings furnish fundamental insights into the dynamics of the SEI and illustrate a path forward towards a predictive understanding of electrochemical passivation.