Bond Valence Pathway Analyzer-An Automatic Rapid Screening Tool for Fast Ion Conductors within softBV

Solid-state fast ionic conductors are of great interest due to their application potential enabling the development of safer high-performance energy and conversion systems ranging from batteries through supercapacitors to fuel cells, electrolyzers, and novel neuromorphic devices. However, identifying fast ion conductors has remained a slow trial-and-error search process. High-throughput computational screening methods such as our bond valence site energy method can significantly accelerate this materials design, but their implementation not only needs to be computationally efficient and dependable but also simple to be used by experimentalists in order to find widespread usage for guiding experimental efforts to promising classes of candidate materials. To bridge the current gap between computational method developers and application-oriented users, we combine the computationally low-cost bond valence site energy calculations in our softBV software tool using a new automated pathway analysis tool-the bond valence pathway analyzer (BVPA). The integration of BVPA gives rapid comprehensive access to and simplifies the visualization of the desired information on the characteristics of ion transport properties in candidate materials. Examples for the main application of identifying suitable structure types for fast ion transport as solid electrolytes or mixed conducting electrode materials with high-rate capability are given. A new dopant predictor further simplifies defect engineering of the candidate systems by automatically suggesting suitable substitutional dopants for each site in the structure based on a new machine-learned approach.

Automated summary

Solid-state fast ionic conductors are of great interest for developing safer, high-performance energy conversion systems. High-throughput computational screening methods can accelerate materials design, while the new automated pathway analysis tool BVPA simplifies the analysis of ion transport properties in candidate materials. The new dopant predictor automatically suggests suitable substitutional dopants for candidate systems.