Combinatorial impedance spectroscopy with Bayesian analysis for triple ionic-electronic conducting perovskites

Abstract

Triple ionic-electronic conducting oxides (TIECs) show great promise in high-temperature electrochemical applications, including ceramic fuel cells and electrolyzers. The transport properties and electrochemical activity of TIECs strongly depend on chemical composition and environmental conditions, such as operating temperature and gas environment. Here, this dependency is investigated in a large family of TIEC oxide perovskite materials via combinatorial experimental methods and multidimensional Bayesian analysis. In total, more than 2500 impedance spectra are collected at three temperatures under dry air and humid N₂ atmospheres from 432 distinct Ba(Co,Fe,Zr,Y)O_3−δ (BCFZY) compositions that were synthesized by pulsed laser deposition. This study provides insight on the trends governing electrochemical performance. Combinatorial experiments demonstrate that Co-rich compositions achieve the lowest overall polarization resistance under both dry air and humid N₂, while Fe substitution may increase polarization resistance. Hierarchical Bayesian analysis indicates that the performance-limiting process depends on the chemical composition, measurement temperature, and atmospheric humidity. This work provides a map of electronic properties of materials in the BCFZY perovskite family under conditions that are relevant to their application as air electrodes for protonic ceramic fuel cells and electrolyzers, and demonstrates a unique approach to studying TIECs that combines combinatorial experiments and Bayesian analysis.