Abstract
DFTB+ is a versatile community developed open source software package offering fast and efficient methods for carrying out atomistic quantum mechanical simulations. By implementing various methods approximating density functional theory (DFT), such as the density functional based tight binding (DFTB) and the extended tight binding method, it enables simulations of large systems and long timescales with reasonable accuracy while being considerably faster for typical simulations than the respective ab initio methods. Based on the DFTB framework, it additionally offers approximated versions of various DFT extensions including hybrid functionals, time dependent formalism for treating excited systems, electron transport using non-equilibrium Green's functions, and many more. DFTB+ can be used as a user-friendly standalone application in addition to being embedded into other software packages as a library or acting as a calculation-server accessed by socket communication. We give an overview of the recently developed capabilities of the DFTB+ code, demonstrating with a few use case examples, discuss the strengths and weaknesses of the various features, and also discuss on-going developments and possible future perspectives.
Original language | English |
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Article number | 124101 |
Journal | Journal of Chemical Physics |
Volume | 152 |
Issue number | 12 |
DOIs | |
State | Published - Mar 31 2020 |
Funding
The authors, especially B. Hourahine and B. Aradi, are thankful to Gotthard Seifert for his suggestions and insights into density functional tight binding throughout the development of the DFTB+ code. B. Hourahine acknowledges the EPSRC (Grant No. EP/P015719/1) for financial support. B. Aradi and T. Frauenheim acknowledge the research training group DFG-RTG 2247 (QM3). A. Buccheri acknowledges the EPSRC (Grant No. EP/P022308/1). C. Camacho acknowledges financial support from the Vice-Rectory for research of the University of Costa Rica (Grant No. 115-B9-461) and the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory (ORNL), which is managed by UT-Battelle, LLC, for DOE under Contract No. DE-AC05-00OR22725. S. Irle acknowledges support from the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division, Geoscience Program. M. Y. Deshaye and T. Kowalczyk acknowledge support from a National Science Foundation RUI Award (No. CHE-1664674) and a CAREER Award (No. DMR-1848067). T. Kowalczyk is a Cottrell Scholar of the Research Corporation for Science Advancement. T. Dumitrică was supported by the National Science Foundation (Grant No. CMMI-1332228). R. J. Maurer acknowledges support via a UKRI Future Leaders Fellowship (Grant No. MR/S016023/1). A. M. N. Niklasson and C. Negre acknowledge support from the U.S. Department of Energy Office of Basic Energy Sciences (Grant No. FWP LANLE8AN); the U.S. Department of Energy through the Los Alamos National Laboratory; and the Exascale Computing Project (No. 17-SC-20-SC), a collaborative effort of the U.S. Department of Energy, Office of Science and the National Nuclear Security Administration. T. A. Niehaus would like to thank the Laboratoire d’Excellence iMUST for financial support. M. Stöhr acknowledges financial support from the Fonds National de la Recherche, Luxembourg (AFR Ph.D. Grant No. CNDTEC). A. Tkatchenko was supported by the European Research Council (ERC-CoG BeStMo). V. W.-z. Yu was supported by the National Science Foundation (NSF) under Grant No. 1450280 and a fellowship from the Molecular Sciences Software Institute under NSF Grant No. 1547580.
Funders | Funder number |
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AFR | |
ERC-CoG BeStMo | 1450280 |
Molecular Sciences Software Institute | 1547580 |
U.S. Department of Energy Office of Basic Energy Sciences | FWP LANLE8AN |
National Science Foundation | 1848067, CHE-1664674, CMMI-1332228, 1664674, DMR-1848067 |
U.S. Department of Energy | DE-AC05-00OR22725 |
Office of Science | |
Basic Energy Sciences | |
National Nuclear Security Administration | |
Oak Ridge National Laboratory | |
Los Alamos National Laboratory | 17-SC-20-SC |
Horizon 2020 Framework Programme | 725291 |
UK Research and Innovation | MR/S016023/1 |
Engineering and Physical Sciences Research Council | EP/P022308/1, EP/P015719/1 |
European Research Council | |
Fonds National de la Recherche Luxembourg | |
Universidad de Costa Rica | 115-B9-461 |