|About this Abstract
||2020 TMS Annual Meeting & Exhibition
||Algorithm Development in Materials Science and Engineering
||L-4: Classifying Atomic Environments by the Gromov-Wasserstein Distance
||Sakura Kawano, Jeremy K. Mason
|On-Site Speaker (Planned)
Interpreting molecular dynamics simulations usually involves automated classification of local atomic environments to identify regions of interest. Existing approaches are generally limited to a small number of reference structures and only include limited information about the local chemical composition. This work proposes to use a variant of the Gromov-Wasserstein (GW) distance to quantify the difference between a local atomic environment and a set of arbitrary reference environments in a way that is sensitive to atomic displacements, missing atoms, and differences in chemical composition. This involves describing a local atomic environment as a finite metric measure space, with the additional advantages of not requiring the local environment to be centered on an atom and of not making any assumptions about the material class. Numerical examples illustrate the efficiency and versatility of the algorithm.
||Planned: Supplemental Proceedings volume