A statistical understanding of oxygen vacancies in distorted high-entropy perovskite oxides

High-entropy perovskite oxides have emerged as promising electrode materials for solid oxide electrolyzers. However, their compositional complexity makes the formation of oxygen vacancies, which influence properties such as oxygen ionic conductivity and thermal expansion, challenging to predict. Here, we experimentally measure changes in oxygen vacancy concentration for fourteen perovskite oxides with high and low-entropy A-site compositions, finding a dependence on cation size variance in addition to divalent cation fraction. Atomistic simulations using a machine-learned universal interatomic potential reveal cation size mismatches broaden a distribution of vacancy formation energies, shown through statistical thermodynamics to shift bulk formation thermodynamics. Treating oxygen vacancies statistically enables accurate predictions of oxygen vacancy formation compared to traditional models. Practically, increasing the size variance between A-site cations reduces the temperature sensitivity of oxygen vacancy concentrations, making it key for tuning critical properties. More broadly, this study demonstrates statistical treatment of oxygen vacancies is essential for understanding high-entropy perovskite oxides.