EMFDTW: An Automated Crystallographic Identification Tool Supporting Multiple Comparison Criteria

Identification of the same and similar crystal structures assists in searching for duplicate materials data and discovering prototype structures. Although several structure identification methods exist, their requirements for the input information limit their ability to accurately and automatically process structures within big materials databases and especially distinguish disordered ion conductor structures due to the site occupancy uncertainty of migration ions. Here, we introduce an automated crystal structure identification method called EMFDTW, in which a set of eigen-subspace modular functions (EMFs) is derived from a distance matrix incorporating site type identifiers, and then the similarity between them is measured through dynamic time warping (DTW). In this way, not only the conventional spatial sites in the crystal structure but also the atomic attributes (type, occupancy, oxidation state, magnetic moment, etc.) on the sites can be considered as the comparative features. Furthermore, by conducting a skeleton similarity analysis on 113,586 crystal structures sourced from the crystallography open database and the inorganic crystal structure database, we establish a database of 17,340 skeleton prototypes, which paves the way for searching potential ionic conductors. Our work provides an easy-to-use tool to analyze complex crystal structures, providing new insights for the discovery and design of new materials.