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Title: High-throughput DFT calculations of formation energy, stability and oxygen vacancy formation energy of ABO3 perovskites

Journal Article · · Scientific Data
ORCiD logo [1];  [1]
  1. Northwestern Univ., Evanston, IL (United States). Dept. of Materials Science and Engineering
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ABO3 perovskites are oxide materials that are used for a variety of applications such as solid oxide fuel cells, piezo-, ferro-electricity and water splitting. Due to their remarkable stability with respect to cation substitution, new compounds for such applications potentially await discovery. In this work, we present an exhaustive dataset of formation energies of 5,329 cubic and distorted perovskites that were calculated using first-principles density functional theory. In addition to formation energies, several additional properties such as oxidation states, band gap, oxygen vacancy formation energy, and thermodynamic stability with respect to all phases in the Open Quantum Materials Database are also made publicly available. This large dataset for this ubiquitous crystal structure type contains 395 perovskites that are predicted to be thermodynamically stable, of which many have not yet been experimentally reported, and therefore represent theoretical predictions. In conclusion, the dataset thus opens avenues for future use, including materials discovery in many research-active areas.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
Grant/Contract Number:
FG02-07ER46433; AC02-05CH11231
OSTI ID:
1490970
Journal Information:
Scientific Data, Vol. 4; ISSN 2052-4463
Publisher:
Nature Publishing GroupCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 219 works
Citation information provided by
Web of Science

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Cited By (18)

Computational screening of methylammonium based halide perovskites with bandgaps suitable for perovskite-perovskite tandem solar cells journal December 2018
Energy refinement and analysis of structures in the QM9 database via a highly accurate quantum chemical method journal July 2019
Ab initio modeling and design of vanadia-based electrode materials for post-lithium batteries journal December 2019
Mechanism of CO production around oxygen vacancy of LaMnO 3 : an efficient and rapid evaluation of the doping effect on the kinetics and thermodynamic driving force of CO 2 -splitting journal January 2020
Systematic trends in YAlO 3 , SrTiO 3 , BaTiO 3 , BaZrO 3 (001) and (111) surface ab initio calculations journal December 2019
Predictions of new AB O 3 perovskite compounds by combining machine learning and density functional theory journal April 2018
Computational Screening of New Perovskite Materials Using Transfer Learning and Deep Learning journal December 2019
Cubic and tetragonal perovskites from the random phase approximation journal October 2019
A quantum-mechanical investigation of oxygen vacancies and copper doping in the orthorhombic CaSnO 3 perovskite journal January 2018
Photo-sensitizing thin-film ferroelectric oxides using materials databases and high-throughput calculations journal January 2019
Vacancy-engineered catalysts for water electrolysis journal January 2020
Reliable and explainable machine-learning methods for accelerated material discovery journal November 2019
Rapid Discovery of Ferroelectric Photovoltaic Perovskites and Material Descriptors via Machine Learning journal May 2019
Effectiveness of Zr and Hf incorporation into LaCoO 3 towards fast and thermodynamically favorable solar thermochemical CO production studied with density functional theory journal January 2020
Materials with the CrVO 4 structure type as candidate superprotonic conductors journal January 2019
Photocatalytic activity of TiO 2 nanoparticles: a theoretical aspect journal January 2019
Reliable and Explainable Machine Learning Methods for Accelerated Material Discovery text January 2019
Benchmarking Materials Property Prediction Methods: The Matbench Test Set and Automatminer Reference Algorithm text January 2020

Figures / Tables (7)

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36 MATERIALS SCIENCE