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Dataset of theoretical multinary perovskite oxides

Authors :
Zachary J. L. Bare
Ryan J. Morelock
Charles B. Musgrave
Source :
Scientific Data, Vol 10, Iss 1, Pp 1-10 (2023)
Publication Year :
2023
Publisher :
Nature Portfolio, 2023.

Abstract

Abstract 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 $${A}_{x}{A}_{1-x}^{\text{'}}{B}_{y}{B}_{1-y}^{\text{'}}{O}_{3}$$ A x A 1 − x ' B y B 1 − y ' O 3 ) chemical space is underexplored due to the immense number of possible compositions. To expand the number of computed $${A}_{x}{A}_{1-x}^{{\prime} }{B}_{y}{B}_{1-y}^{{\prime} }{O}_{3}$$ A x A 1 − x ′ B y B 1 − y ′ O 3 compounds we report a dataset of 66,516 theoretical multinary oxides, 59,708 of which are perovskites. First, 69,407 $${A}_{0.5}{A}_{0.5}^{{\prime} }{B}_{0.5}{B}_{0.5}^{{\prime} }{O}_{3}$$ A 0.5 A 0.5 ′ B 0.5 B 0.5 ′ O 3 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 (ΔH f ) and decomposition enthalpies (ΔH d ) 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 $${A}_{0.5}{A}_{0.5}^{{\prime} }{B}_{0.5}{B}_{0.5}^{{\prime} }{O}_{3}$$ A 0.5 A 0.5 ′ B 0.5 B 0.5 ′ O 3 perovskite structures using MP-compatible DFT calculations.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20524463
Volume :
10
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Data
Publication Type :
Academic Journal
Accession number :
edsdoj.4858305d5c6454784b07b3394d11587
Document Type :
article
Full Text :
https://doi.org/10.1038/s41597-023-02127-w