EMFDTW: an automated crystallographic identification tool supporting multiple comparison criteria

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dc.contributor.authorHe, Ben_AU
dc.contributor.authorMeng, Yen_AU
dc.contributor.authorGong, Zen_AU
dc.contributor.authorWang, Ken_AU
dc.contributor.authorJiang, Zen_AU
dc.contributor.authorAvdeev, Men_AU
dc.contributor.authorShi, SQen_AU
dc.date.accessioned2024-12-05T23:36:10Zen_AU
dc.date.available2024-12-05T23:36:10Zen_AU
dc.date.issued2024-07-13en_AU
dc.date.statistics2024-11-28en_AU
dc.description.abstractIdentification 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. © 2024 American Chemical Society.en_AU
dc.description.sponsorshipWe would like to thank Dr. Chuanxun Su for fruitful discussion. This work is supported by the National Key Research and Development Program of China (no. 2021YFB3802100) and the National Natural Science Foundation of China (no. 92270124). We appreciate the High Performance Computing Center of Shanghai University, Shanghai Engineering Research Center of Intelligent Computing System (no. 19DZ2252600), and the Shanghai Technical Service Center for Advanced Ceramics Structure Design and Precision Manufacturing (no. 20DZ2294000). All the computations are supported by the Shanghai Technical Service Center of Science and Engineering Computing, Shanghai University.en_AU
dc.identifier.citationHe, B., Meng, Y., Gong, Z., Wang, K., Jiang, Z., Avdeev, M., & Shi, S. (2024). EMFDTW: an automated crystallographic identification tool supporting multiple comparison criteria. Crystal Growth & Design, 24(13), 5559-5568. doi:10.1021/acs.cgd.4c00346en_AU
dc.identifier.issn1528-7483en_AU
dc.identifier.issn1528-7505en_AU
dc.identifier.issue13en_AU
dc.identifier.journaltitleCrystal Growth & Designen_AU
dc.identifier.pagination5559-5568en_AU
dc.identifier.urihttps://doi.org/10.1021/acs.cgd.4c00346en_AU
dc.identifier.urihttps://apo.ansto.gov.au/handle/10238/15795en_AU
dc.identifier.volume24en_AU
dc.languageEnglishen_AU
dc.language.isoenen_AU
dc.publisherAmerican Chemical Societyen_AU
dc.subjectIonsen_AU
dc.subjectCrystal structureen_AU
dc.subjectMolecular structureen_AU
dc.subjectMaterialsen_AU
dc.subjectCrystallographyen_AU
dc.subjectMigrationen_AU
dc.titleEMFDTW: an automated crystallographic identification tool supporting multiple comparison criteriaen_AU
dc.typeJournal Articleen_AU
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