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Abstract
Calculations of point defect energetics with Density Functional Theory (DFT) can provide valuable insight into several optoelectronic, thermodynamic, and kinetic properties. These calculations commonly use methods ranging from semi-local functionals with a-posteriori corrections to more computationally intensive hybrid functional approaches. For applications of DFT-based high-throughput computation for data-driven materials discovery, point defect properties are of interest, yet are currently excluded from available materials databases. This work presents a benchmark analysis of automated, semi-local point defect calculations with a-posteriori corrections, compared to 245 “gold standard” hybrid calculations previously published. We consider three different a-posteriori correction sets implemented in an automated workflow, and evaluate the qualitative and quantitative differences among four different categories of defect information: thermodynamic transition levels, formation energies, Fermi levels, and dopability limits. We highlight qualitative information that can be extracted from high-throughput calculations based on semi-local DFT methods, while also demonstrating the limits of quantitative accuracy.
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1 Lawrence Berkeley National Laboratory, Materials Sciences Division, Berkeley, USA (GRID:grid.184769.5) (ISNI:0000 0001 2231 4551); University of California, Department of Materials Science and Engineering, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878)
2 Harvard University, John A. Paulson School of Engineering and Applied Sciences, Cambridge, USA (GRID:grid.38142.3c) (ISNI:000000041936754X)
3 An-Najah National University, Department of Physics, Nablus, Palestine (GRID:grid.11942.3f) (ISNI:0000 0004 0631 5695); Université Catholique de Louvain, Institute of Condensed Matter and Nanosciences, Louvain-la-Neuve, Belgium (GRID:grid.7942.8) (ISNI:0000 0001 2294 713X)
4 NTNU Norwegian University of Science and Technology, Department of Materials Science and Engineering, Trondheim, Norway (GRID:grid.5947.f) (ISNI:0000 0001 1516 2393)
5 Lawrence Berkeley National Laboratory, Energy Technologies Area, Berkeley, USA (GRID:grid.184769.5) (ISNI:0000 0001 2231 4551)
6 University College London, Department of Chemistry, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201); University College London, Thomas Young Centre, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201); Diamond Light Source Ltd., Diamond House, Didcot, UK (GRID:grid.18785.33) (ISNI:0000 0004 1764 0696)
7 Université Catholique de Louvain, Institute of Condensed Matter and Nanosciences, Louvain-la-Neuve, Belgium (GRID:grid.7942.8) (ISNI:0000 0001 2294 713X)
8 Lawrence Berkeley National Laboratory, Materials Sciences Division, Berkeley, USA (GRID:grid.184769.5) (ISNI:0000 0001 2231 4551)
9 Lawrence Livermore National Laboratory, Livermore, USA (GRID:grid.250008.f) (ISNI:0000 0001 2160 9702)
10 University of California, Department of Materials Science and Engineering, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); Lawrence Berkeley National Laboratory, Molecular Foundry, Berkeley, USA (GRID:grid.184769.5) (ISNI:0000 0001 2231 4551)
11 Université Catholique de Louvain, Institute of Condensed Matter and Nanosciences, Louvain-la-Neuve, Belgium (GRID:grid.7942.8) (ISNI:0000 0001 2294 713X); Dartmouth College, Thayer School of Engineering, Hanover, USA (GRID:grid.254880.3) (ISNI:0000 0001 2179 2404)