Macro-scale battery aging models rely on empirical parameters to describe Solid Electrolyte Interphase (SEI) growth — a picosecond-timescale electrochemical phenomenon that classical molecular dynamics cannot reach and ab-initio MD cannot sustain. This project closes that gap by implementing a reactive-step molecular-dynamics (rs@md) framework that couples classical MD with reaction probabilities derived from transition-state theory. Density-functional theory is used to compute activation barriers for elementary SEI-formation reactions starting from electron transfer at the graphite anode; rs@md simulations of a graphite/electrolyte cell then track SEI film growth and yield effective reaction and Li-ion diffusion rates. The extracted micro-kinetic parameters serve as physics-based inputs to the macroscopic P2D model used in the doctoral research.

Macro-scale battery aging models rely on empirical parameters to describe Solid Electrolyte Interphase (SEI) growth — a picosecond-timescale electrochemical phenomenon that classical molecular dynamics cannot reach and ab-initio MD cannot sustain. This project closes that gap by implementing a reactive-step molecular-dynamics (rs@md) framework that couples classical MD with reaction probabilities derived from transition-state theory. Density-functional theory is used to compute activation barriers for elementary SEI-formation reactions starting from electron transfer at the graphite anode; rs@md simulations of a graphite/electrolyte cell then track SEI film growth and yield effective reaction and Li-ion diffusion rates. The extracted micro-kinetic parameters serve as physics-based inputs to the macroscopic P2D model used in the doctoral research.