Insights into oxygen vacancies from high-throughput first-principles calculations
نویسندگان
چکیده
Oxygen vacancies play significant roles in various properties of oxide materials. Therefore, insights into the oxygen can facilitate discovery better To achieve this, we developed codes for high-throughput point-defect calculations and applied them to characterize 937 oxides. From resulting large dataset, analyzed vacancy structures formation energies constructed machine-learning regression models predict energies. We have found that are predicted using random forest with accuracies 0.27--0.44 eV depending on charge states. Analyses importance descriptors show neutral mainly determined by orbital characteristics conduction-band minima, stability, band gaps, whereas those doubly charged defects factors related electrostatic energy. These datasets publicly available, a graphical user interface is available analyze calculation results.
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ژورنال
عنوان ژورنال: Physical Review Materials
سال: 2021
ISSN: ['2476-0455', '2475-9953']
DOI: https://doi.org/10.1103/physrevmaterials.5.123803