Predicting ion diffusion from the shape of potential energy landscapes, Materials Chemistry, ChemRxiv

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.

York Lab

Published Papers – Computational Chemical Science Center

Unified quantum theory of electrochemical kinetics by coupled ion

Hibbitts Group Publications

Published Papers – Computational Chemical Science Center

Publications Computational Biophysics Group

Classical and reactive molecular dynamics: Principles and

OpenKIM · SNAP ThompsonSwilerTrott 2015 Ta MO_359768485367_000 MO_359768485367 · Interatomic Potentials and Force Fields

Unified quantum theory of electrochemical kinetics by coupled ion–electron transfer - Faraday Discussions (RSC Publishing) DOI:10.1039/D3FD00108C

PDF) Neural Network Potentials for Accelerated Metadynamics of

Entropy, Free Full-Text

Applications of Artificial Intelligence and Machine Learning Algorithms to Crystallization

Energy profile (chemistry) - Wikipedia