Since 2012, when the Materials Genome Initiative (MGI) was announced, combining materials databases with high-throughput calculations has become an effective approach to accelerate materials discovery. We found that most MGI platforms concentrate on materials properties including formation energy, band gap, band structure, elastic constant etc. that are available through high-throughput DFT calculations, but systematic computational information on ion-transport properties remained sparse. To fill this gap, our team envisaged to develop a high-throughput screening platform for solid electrolytes, which comprises not only a materials database, but also computational screening tools to assess ion-transport-related properties and a task management system achieving high-throughput calculation to automate the characterization of materials.

Over the past five years our team bundled efforts to augment the simple bond valence (BV) approach that derived from Linus Pauling’s electrostatic valence principle (1929) into an effective algorithm for high-throughput prediction of ion migration paths and the energy barriers therein. To this end we developed the BVSE calculation program based on our previously formulated bond valence site energy model. Moreover, we developed crystal structure geometric analysis program CAVD, which further accelerates the prediction of the ion-transport network in a crystal structure. These two methods, BVSE and CAVD, provide complementary information on the suitability of a crystal structure for high mobility of ions, which is a prerequisite for solid electrolytes and electrode materials for rechargeable metal-ion batteries.

In our paper published in Scientific Data, we described a high-throughput screening platform for solid electrolytes (SPSE). This SPSE platform, which is open to the public online, integrates geometric analysis (CAVD) and bond valence site energy (BVSE) calculations with a material database (https://www.bmaterials.cn). Furthermore, the SPSE can not only be used for empirical screening to identify promising ion-conducting solids, but uses the results of this pre-screening to guide and prepare the input for more precise DFT calculations, such as Nudged Elastic Band analysis as implemented in the Vienna Ab Initio Simulation Package (VASP).

The approach in SPSE thus has a hierarchical structure, which includes rapid empirical methods (BVSE and CAVD), more precise DFT calculations, and a database for storing and retrieving results. The SPSE database is based on FAIR principles, which ensures the processed and produced data to be findable, accessible, interoperable, and reusable and already contains tens of thousands of structure entries and hundreds of thousands of computed data sets, which can be obtained through accessing our platform.

The SPSE platform is the result of a large-scale research collaboration among eight institutions in three countries and we hope it will be useful to accelerate materials design in energy storage systems. Therefore we look forward to wide use of this platform and feedback from the energy research community.