Perovskite oxides (ternary chemical formula ABO3) are a diverse class of materials with applications including heterogeneous catalysis, solid-oxide fuel cells, thermochemical conversion, and oxygen transport membranes. However, their multicomponent (chemical formula AxA1−x'ByB1−y'O3) chemical space is underexplored due to the immense number of possible compositions. To expand the number of computed AxA1−x′ByB1−y′O3 compounds we report a dataset of 66,516 theoretical multinary oxides, 59,708 of which are perovskites. First, 69,407 A0.5A0.5′B0.5B0.5′O3 compositions were generated in the a − b + a − Glazer tilting mode using the computationally-inexpensive Structure Prediction and Diagnostic Software (SPuDS) program. Next, we optimized these structures with density functional theory (DFT) using parameters compatible with the Materials Project (MP) database. Our dataset contains these optimized structures and their formation (ΔHf) and decomposition enthalpies (ΔHd) computed relative to MP tabulated elemental references and competing phases, respectively. This dataset can be mined, used to train machine learning models, and rapidly and systematically expanded by optimizing more SPuDS-generated A0.5A0.5′B0.5B0.5′O3 perovskite structures using MP-compatible DFT calculations.
CITATION STYLE
Bare, Z. J. L., Morelock, R. J., & Musgrave, C. B. (2023). Dataset of theoretical multinary perovskite oxides. Scientific Data, 10(1). https://doi.org/10.1038/s41597-023-02127-w
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