Predicting Ion Diffusion from the Shape of Potential Energy Landscapes
We present an efficient method to compute diffusion coefficients of multiparticle 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 1 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 the density functional level of theory.
WOS:001139439000001
2023-12-19
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Funder | Grant Number |
National Center of Competence in Research Materials? Revolution: Computational Design and Discovery of Novel Materials | 2019-05366 |
Swedish Research Council | 50098-1 |
Swedish Energy Agency | |
Center for Applied Mathematics (CIM) at Uppsala University | |
Swedish National Strategic e-Science programme (eSSENCE) | 205602 |
NCCR MARVEL, a National Centre of Competence in Research - Swiss National Science Foundation | |