In this study, we used a combination of density functional theory with Hubbard U correction (DFT+U) and machine learning (ML) to accurately predict the band gaps and lattice parameters of metal oxides: TiO2 (rutile and anatase), cubic ZnO, cubic ZnO2, cubic CeO2, and cubic ZrO2. Our results show that including Up values for oxygen 2p orbitals alongside Ud/f for metal 3d or 4f orbitals significantly enhances the accuracy of these predictions. Through extensive DFT+U calculations, we identify optimal (Up, Ud/f) integer pairs that closely reproduce experimentally measured band gaps and lattice parameters for each oxide: (8 eV, 8 eV) for rutile TiO2; (3 eV, 6 eV) for anatase TiO2; (6 eV, 12 eV) for c-ZnO; (10 eV, 10 eV) for c-ZnO2; (9 eV, 5 eV) for c-ZrO2; and (7 eV, 12 eV) for c-CeO2. Our ML analysis showed that simple supervised ML models can closely reproduce these DFT+U results at a fraction of the computational cost and generalize well to related polymorphs. Our approach builds on existing high-throughput DFT+U frameworks by providing fast pre-DFT estimates of structural properties and band gaps. Since this work does not aim to improve the underlying DFT+U method, the ML model shares its limitations. We also note that the reported values of Up strongly depend on the choice of correlated orbitals, and caution is recommended with a different choice of correlated orbitals.
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Extensive Benchmarking of DFT+U Calculations for Predicting Band Gaps
Accurate computational predictions of band gaps are of practical importance to the modeling and development of semiconductor technologies, such as (opto)electronic devices and photoelectrochemical cells. Among available electronic-structure methods, density-functional theory (DFT) with the Hubbard U correction (DFT+U) applied to band edge states is a computationally tractable approach to improve the accuracy of band gap predictions beyond that of DFT calculations based on (semi)local functionals. At variance with DFT approximations, which are not intended to describe optical band gaps and other excited-state properties, DFT+U can be interpreted as an approximate spectral-potential method when U is determined by imposing the piecewise linearity of the total energy with respect to electronic occupations in the Hubbard manifold (thus removing self-interaction errors in this subspace), thereby providing a (heuristic) justification for using DFT+U to predict band gaps. However, it is still frequent in the literature to determine the Hubbard U parameters semiempirically by tuning their values to reproduce experimental band gaps, which ultimately alters the description of other total-energy characteristics. Here, we present an extensive assessment of DFT+U band gaps computed using self-consistent ab initio U parameters obtained from density-functional perturbation theory to impose the aforementioned piecewise linearity of the total energy. The study is carried out on 20 compounds containing transition-metal or p-block (group III-IV) elements, including oxides, nitrides, sulfides, oxynitrides, and oxysulfides. By comparing DFT+U results obtained using nonorthogonalized and orthogonalized atomic orbitals as Hubbard projectors, we find that the predicted band gaps are extremely sensitive to the type of projector functions and that the orthogonalized projectors give the most accurate band gaps, in satisfactory agreement with experimental data. This work demonstrates that DFT+U may serve as a useful method for high-throughput workflows that require reliable band gap predictions at moderate computational cost.
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- Award ID(s):
- 1729338
- PAR ID:
- 10223643
- Date Published:
- Journal Name:
- Applied Sciences
- Volume:
- 11
- Issue:
- 5
- ISSN:
- 2076-3417
- Page Range / eLocation ID:
- 2395
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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