Abstract

Oxygen vacancies play significant roles in various properties of oxide materials. Therefore, insights into the oxygen vacancies can facilitate the discovery of better oxide materials. To achieve this, we developed codes for high-throughput point-defect calculations and applied them to characterize oxygen vacancies in 937 oxides. From the resulting large dataset, we analyzed the vacancy structures and formation energies and constructed machine-learning regression models to predict vacancy formation energies. We have found that the vacancy formation energies are predicted using the random forest regression models with accuracies of 0.27--0.44 eV depending on the charge states. Analyses of the importance of the descriptors show that the formation energies of the neutral vacancies are mainly determined by the orbital characteristics of the conduction-band minima, the oxide stability, and the band gaps, whereas those of the doubly charged defects are determined by factors related to electrostatic energy. These codes and datasets are publicly available, and a graphical user interface is available to analyze the calculation results.

Highlights

  • IntroductionOxygen vacancies (VO) play significant roles in various physical and chemical properties of metal oxides, including electronic conductivity, ion diffusion, superconductivity, catalytic and photocatalytic activity, and optical properties

  • IMPORTANCE OF HIGH-THROUGHPUT POINT DEFECT CALCULATIONSOxygen vacancies (VO) play significant roles in various physical and chemical properties of metal oxides, including electronic conductivity, ion diffusion, superconductivity, catalytic and photocatalytic activity, and optical properties

  • The targeted oxides were retrieved from the Materials Project database (MPD) [17] using its application programming interface implemented in PYMATGEN [18], at which the formation energies in the MPD were corrected using the empirical scheme to reproduce the experimental enthalpies at 298 K [19]

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Summary

Introduction

Oxygen vacancies (VO) play significant roles in various physical and chemical properties of metal oxides, including electronic conductivity, ion diffusion, superconductivity, catalytic and photocatalytic activity, and optical properties. These properties in turn determine the suitability of metal oxides for specific applications. Insights into oxygen vacancies, including their local structures and formation energies, can facilitate the discovery of better oxide materials. Experimental investigations of VO are challenging because the electronic and atomic structures of defects are not easy to determine, even today [5]. Accurate predictions of point-defect properties using first-principles calculations have become plausible with recent improvements in computational power and techniques

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