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Benchmarking density functional tight binding models for barrier heights and reaction energetics of organic molecules

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2017
nihms884810.pdf (1.161Mb)
Authors
Gruden, Maja
Anđelković, Ljubica
Jissy, Akkarapattiakal Kuriappan
Stepanović, Stepan
Zlatar, Matija
Cui, Qiang
Elstner, Marcus
Article (Accepted Version)
,
John Wiley & Sons, Inc.
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Abstract
Density Functional Tight Binding (DFTB) models are two to three orders of magnitude faster than ab initio and Density Functional Theory (DFT) methods and therefore are particularly attractive in applications to large molecules and condensed phase systems. To establish the applicability of DFTB models to general chemical reactions, we conduct benchmark calculations for barrier heights and reaction energetics of organic molecules using existing databases and several new ones compiled in this study. Structures for the transition states and stable species have been fully optimized at the DFTB level, making it possible to characterize the reliability of DFTB models in a more thorough fashion compared to conducting single point energy calculations as done in previous benchmark studies. The encouraging results for the diverse sets of reactions studied here suggest that DFTB models, especially the most recent third-order version (DFTB3/3OB augmented with dispersion correction), in most cases p...rovide satisfactory description of organic chemical reactions with accuracy almost comparable to popular DFT methods with large basis sets, although larger errors are also seen for certain cases. Therefore, DFTB models can be effective for mechanistic analysis (e.g., transition state search) of large (bio)molecules, especially when coupled with single point energy calculations at higher levels of theory.

Keywords:
DFTB / transition state optimization / barrier heights / reaction energies
Source:
Journal of Computational Chemistry, 2017, 38, 25, 2171-2185
Publisher:
  • Wiley, Hoboken
Projects:
  • Rational design and synthesis of biologically active and coordination compounds and functional materials, relevant for (bio)nanotechnology (RS-172035)
  • National Institutes of Health (NIH) [R01-GM106443]
  • German Academic Exchange Service (DAAD)
  • Serbian-German bilateral project [451-03-01038/2015-09/7]
Note:
  • This is the peer-reviewed version of the following article: Gruden, M., Andjelkovic, L., Jissy, A.K., Stepanović, S., Zlatar, M., Cui, Q., Elstner, M., Journal of Computational Chemistry, 2017, 38 (25), pp. 2171-2185. which has been published in final form at https://doi.org/10.1002/jcc.24866. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
  • http://cer.ihtm.bg.ac.rs/handle/123456789/2131

DOI: 10.1002/jcc.24866

ISSN: 0192-8651

PubMed: 28736893

WoS: 000407616400005

Scopus: 2-s2.0-85027395007
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URI
http://cer.ihtm.bg.ac.rs/handle/123456789/2734
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