Prediction of perovskite-related structures in ACuO$_{3-x}$ (A $=$ Ca, Sr, Ba, Sc, Y, La) using density functional theory and Bayesian optimization

Oxygen vacancy ordering in perovskite-type transition-metal oxides plays an important role in the emergence of exotic electronic properties, as typified by superconducting cuprates. In this study, we predict the stability of oxygen-deficient perovskite structures in ACuO$_{3-x}$ (A $=$ Ca, Sr, Ba, Sc, Y, La) by density functional theory calculation. We introduce a combination of the cluster expansion method, Gaussian process, and Bayesian optimization to find stable oxygen-deficient structures among a considerable number of candidates. Our calculations not only reproduce the reported structures but suggest the presence of several unknown oxygen-deficient perovskite structures, some of which are stabilized at high pressures. This work demonstrates the great applicability of the present computational procedure for the elucidation of the structural stability of strongly correlated oxides with a large tolerance to oxygen deficiency.