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.

Details

Title
High-throughput calculations of charged point defect properties with semi-local density functional theory—performance benchmarks for materials screening applications
Author
Broberg, Danny 1 ; Bystrom, Kyle 2   VIAFID ORCID Logo  ; Srivastava, Shivani 1 ; Dahliah, Diana 3 ; Williamson, Benjamin A. D. 4 ; Weston, Leigh 5 ; Scanlon, David O. 6   VIAFID ORCID Logo  ; Rignanese, Gian-Marco 7   VIAFID ORCID Logo  ; Dwaraknath, Shyam 8   VIAFID ORCID Logo  ; Varley, Joel 9 ; Persson, Kristin A. 10   VIAFID ORCID Logo  ; Asta, Mark 1 ; Hautier, Geoffroy 11 

 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) 
 Harvard University, John A. Paulson School of Engineering and Applied Sciences, Cambridge, USA (GRID:grid.38142.3c) (ISNI:000000041936754X) 
 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) 
 NTNU Norwegian University of Science and Technology, Department of Materials Science and Engineering, Trondheim, Norway (GRID:grid.5947.f) (ISNI:0000 0001 1516 2393) 
 Lawrence Berkeley National Laboratory, Energy Technologies Area, Berkeley, USA (GRID:grid.184769.5) (ISNI:0000 0001 2231 4551) 
 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) 
 Université Catholique de Louvain, Institute of Condensed Matter and Nanosciences, Louvain-la-Neuve, Belgium (GRID:grid.7942.8) (ISNI:0000 0001 2294 713X) 
 Lawrence Berkeley National Laboratory, Materials Sciences Division, Berkeley, USA (GRID:grid.184769.5) (ISNI:0000 0001 2231 4551) 
 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) 
Pages
72
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20573960
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2809342292
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.