Accelerated Discovery of Proton-Conducting Perovskite Oxide by Capturing Physicochemical Fundamentals of Hydration

Proton-conducting perovskite oxides are attractive as electrolytes for environmentally friendly electrochemical devices, giving rise to a demand for a variety of oxides. However, complex phenomena occurring during hydration present challenges for expanding the materials library. Herein, we demonstrate the accelerated discovery of a proton-conducting oxide using data-driven structure-property maps for hydration of 8613 hypothetical perovskite oxides in descriptor spaces characterized as important by gradient boosting regressors. We constructed trustworthy hydration training data sets for 65 compounds, including literature data, by performing thermogravimetry measurements on 22 perovskites. Knowledge-based target variable engineering was necessary to capture the physicochemical fundamentals of hydration and attain high accuracy for predicting proton concentration against temperature in unknown compositions extrapolated from training data sets. The model nominates the SrSnO3 host, which was not previously recognized for proton incorporation or proton conduction, and SrSn0.8Sc0.2O3-delta demonstrated proton incorporation and conduction. The results are promising for syrthesis accelerating development and applications of proton-conducting oxides.

Automated summary

Accelerated discovery of a proton-conducting oxide was demonstrated using data-driven structure-property maps for hydration of hypothetical perovskite oxides. This approach involved constructing trustworthy hydration training data sets and knowledge-based target variable engineering to achieve high accuracy in predicting proton concentration against temperature in unknown compositions extrapolated from the training data sets. The results are promising for speeding up the development and applications of proton-conducting oxides.