Predicting ion diffusion from the shape of potential energy landscapes

18 October 2023, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


We present an efficient method to compute diffusion coefficients of multi-particle systems with strong interactions directly from the geometry and topology of the potential energy field of the migrating particles. The approach is tested on Li-ion diffusion in crystalline inorganic solids, predicting Li-ion diffusion coefficients within one order of magnitude of molecular dynamics simulations at the same level of theory while being several orders of magnitude faster. The speed and transferability of our workflow make it well suited for extensive and efficient screening studies of crystalline solid-state ion conductor candidates and promise to serve as a platform for diffusion prediction even up to density functional level of theory.


ion diffusion
transistion state theory
kinetic monte carlo
multi-scale modeling
solid-state electrolytes
Li-ion batteries

Supplementary materials

Supporting Information: Predicting ion diffusion from the shape of potential energy landscapes
dditional computational details and analysis results.


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