TY - JOUR
T1 - p yGWBSE
T2 - a high throughput workflow package for GW-BSE calculations
AU - Biswas, Tathagata
AU - Singh, Arunima K.
N1 - Funding Information:
This work was supported by ULTRA, an Energy Frontier Research Center funded by the U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES), under Award # DE-SC0021230. In addition, Singh acknowledges support by the Arizona State University start-up funds. The authors acknowledge the San Diego Supercomputer Center under the NSF-XSEDE Award No. DMR150006 and the Research Computing at Arizona State University for providing HPC resources. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. The authors also thank Tara M. Boland, Adway Gupta, Akash Patel, and Cody Milne for testing the code and for helpful discussions.
Funding Information:
This work was supported by ULTRA, an Energy Frontier Research Center funded by the U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES), under Award # DE-SC0021230. In addition, Singh acknowledges support by the Arizona State University start-up funds. The authors acknowledge the San Diego Supercomputer Center under the NSF-XSEDE Award No. DMR150006 and the Research Computing at Arizona State University for providing HPC resources. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. The authors also thank Tara M. Boland, Adway Gupta, Akash Patel, and Cody Milne for testing the code and for helpful discussions.
Publisher Copyright:
© 2023, The Author(s).
PY - 2023/12
Y1 - 2023/12
N2 - We develop an open-source python workflow package, pyGWBSE to perform automated first-principles calculations within the GW-BSE (Bethe-Salpeter) framework. GW-BSE is a many body perturbation theory based approach to explore the quasiparticle (QP) and excitonic properties of materials. GW approximation accurately predicts bandgaps of materials by overcoming the bandgap underestimation issue of the more widely used density functional theory (DFT). BSE formalism produces absorption spectra directly comparable with experimental observations. pyGWBSE package achieves complete automation of the entire multi-step GW-BSE computation, including the convergence tests of several parameters that are crucial for the accuracy of these calculations. pyGWBSE is integrated with Wannier90, to generate QP bandstructures, interpolated using the maximally-localized wannier functions. pyGWBSE also enables the automated creation of databases of metadata and data, including QP and excitonic properties, which can be extremely useful for future material discovery studies in the field of ultra-wide bandgap semiconductors, electronics, photovoltaics, and photocatalysis.
AB - We develop an open-source python workflow package, pyGWBSE to perform automated first-principles calculations within the GW-BSE (Bethe-Salpeter) framework. GW-BSE is a many body perturbation theory based approach to explore the quasiparticle (QP) and excitonic properties of materials. GW approximation accurately predicts bandgaps of materials by overcoming the bandgap underestimation issue of the more widely used density functional theory (DFT). BSE formalism produces absorption spectra directly comparable with experimental observations. pyGWBSE package achieves complete automation of the entire multi-step GW-BSE computation, including the convergence tests of several parameters that are crucial for the accuracy of these calculations. pyGWBSE is integrated with Wannier90, to generate QP bandstructures, interpolated using the maximally-localized wannier functions. pyGWBSE also enables the automated creation of databases of metadata and data, including QP and excitonic properties, which can be extremely useful for future material discovery studies in the field of ultra-wide bandgap semiconductors, electronics, photovoltaics, and photocatalysis.
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U2 - 10.1038/s41524-023-00976-y
DO - 10.1038/s41524-023-00976-y
M3 - Article
AN - SCOPUS:85148427268
SN - 2057-3960
VL - 9
JO - npj Computational Materials
JF - npj Computational Materials
IS - 1
M1 - 22
ER -