Journal
SCIENTIFIC DATA
Volume 7, Issue 1, Pages -Publisher
NATURE RESEARCH
DOI: 10.1038/s41597-020-0474-y
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Funding
- National Key Research and Development Program of China [2017YFB0701600]
- National Natural Science Foundation of China [51622207, 11874254, U1630134]
- Shanghai Municipal Science and Technology Commission [19DZ2252600]
- NUS strategic programme
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The combination of a materials database with high-throughput ion-transport calculations is an effective approach to screen for promising solid electrolytes. However, automating the complicated preprocessing involved in currently widely used ion-transport characterization algorithms, such as the first-principles nudged elastic band (FP-NEB) method, remains challenging. Here, we report on high-throughput screening platform for solid electrolytes (SPSE) that integrates a materials database with hierarchical ion-transport calculations realized by implementing empirical algorithms to assist in FP-NEB completing automatic calculation. We first preliminarily screen candidates and determine the approximate ion-transport paths using empirical both geometric analysis and the bond valence site energy method. A chain of images are then automatically generated along these paths for accurate FP-NEB calculation. In addition, an open web interface is actualized to enable access to the SPSE database, thereby facilitating machine learning. This interactive platform provides a workflow toward high-throughput screening for future discovery and design of promising solid electrolytes and the SPSE database is based on the FAIR principles for the benefit of the broad research community.
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