High-throughput screening platform for solid electrolytes combining hierarchical ion-transport prediction algorithms
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Date
2020-05-21
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Nature
Abstract
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. © 2020, The Author(s)
Description
Keywords
Radioisotope batteries, Electrolytes, Computerized simulation, Solid electrolytes, Crystal structure, Monte Carlo Method
Citation
He, B., Chi, S., Ye, A., Mi, P., Zhang, L., Pu, B., Zou, Z., Ran, Y., Zhao, Q., Wang, D., Zhang, W., Zhao, J., Adams, S., Avdeev, M., & Shi, S. (2020). High-throughput screening platform for solid electrolytes combining hierarchical ion-transport prediction algorithms. Scientific Data, 7, 1-14, 151. doi:10.1038/s41597-020-0474-y