Efficient and improved prediction of the band offsets at semiconductor heterojunctions from meta-GGA density functionals: A benchmark study
Ghosh A, Jana S, Rauch T, Tran F, Marques MA, Botti S, Constantin LA, Niranjan MK, Samal P (2022)
Publication Type: Journal article
Publication year: 2022
Journal
Book Volume: 157
Article Number: 124108
Journal Issue: 12
DOI: 10.1063/5.0111693
Abstract
Accurate theoretical prediction of the band offsets at interfaces of semiconductor heterostructures can often be quite challenging. Although density functional theory has been reasonably successful to carry out such calculations, efficient, accurate semilocal functionals are desirable to reduce the computational cost. In general, the semilocal functionals based on the generalized gradient approximation (GGA) significantly underestimate the bulk bandgaps. This, in turn, results in inaccurate estimates of the band offsets at the heterointerfaces. In this paper, we investigate the performance of several advanced meta-GGA functionals in the computational prediction of band offsets at semiconductor heterojunctions. In particular, we investigate the performance of r2SCAN (two times revised strongly constrained and appropriately normed functional), rMGGAC (revised semilocal functional based on cuspless hydrogen model and Pauli kinetic energy density functional), mTASK (modified Aschebrock and Kümmel meta-GGA functional), and local modified Becke-Johnson exchange-correlation functionals. Our results strongly suggest that these meta-GGA functionals for supercell calculations perform quite well, especially, when compared to computationally more demanding GW calculations. We also present band offsets calculated using ionization potentials and electron affinities, as well as band alignment via the branch point energies. Overall, our study shows that the aforementioned meta-GGA functionals can be used within the density functional theory framework to estimate the band offsets in semiconductor heterostructures with predictive accuracy.
Involved external institutions
Indian Institute of Technology Hyderabad
India (IN)
Ohio State University
United States (USA) (US)
Friedrich-Schiller-Universität Jena
Germany (DE)
VASP Software
Austria (AT)
European Theoretical Spectroscopy Facility (ETSF)
Belgium (BE)
Consiglio Nazionale delle Ricerche (CNR) / National Research Council of Italy
Italy (IT)
India (IN)
Ohio State University
United States (USA) (US)
Friedrich-Schiller-Universität Jena
Germany (DE)
VASP Software
Austria (AT)
European Theoretical Spectroscopy Facility (ETSF)
Belgium (BE)
Consiglio Nazionale delle Ricerche (CNR) / National Research Council of Italy
Italy (IT)
How to cite
APA:
Ghosh, A., Jana, S., Rauch, T., Tran, F., Marques, M.A., Botti, S.,... Samal, P. (2022). Efficient and improved prediction of the band offsets at semiconductor heterojunctions from meta-GGA density functionals: A benchmark study. Journal of Chemical Physics, 157(12). https://doi.org/10.1063/5.0111693
MLA:
Ghosh, Arghya, et al. "Efficient and improved prediction of the band offsets at semiconductor heterojunctions from meta-GGA density functionals: A benchmark study." Journal of Chemical Physics 157.12 (2022).
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