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GFN2-xTB—An Accurate and Broadly Parametrized Self-Consistent Tight-Binding Quantum Chemical Method with Multipole Electrostatics and Density-Dependent Dispersion Contributions
Open accessAbstract
An extended semiempirical tight-binding model is presented, which is primarily designed for the fast calculation of structures and noncovalent interaction energies for molecular systems with roughly 1000 atoms. The essential novelty in this so-called GFN2-xTB method is the inclusion of anisotropic second order density fluctuation effects via short-range damped interactions of cumulative atomic multipole moments. Without noticeable increase in the computational demands, this results in a less empirical and overall more physically sound method, which does not require any classical halogen or hydrogen bonding corrections and which relies solely on global and element-specific parameters (available up to radon, Z = 86). Moreover, the atomic partial charge dependent D4 London dispersion model is incorporated self-consistently, which can be naturally obtained in a tight-binding picture from second order density fluctuations. Fully analytical and numerically precise gradients (nuclear forces) are implemented. The accuracy of the method is benchmarked for a wide variety of systems and compared with other semiempirical methods. Along with excellent performance for the "target" properties, we also find lower errors for "off-target" properties such as barrier heights and molecular dipole moments. High computational efficiency along with the improved physics compared to its precursor GFN-xTB makes this method well-suited to explore the conformational space of molecular systems. Significant improvements are furthermore observed for various benchmark sets, which are prototypical for biomolecular systems in aqueous solution.
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Cites
CRC Handbook of Chemistry and Physics
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An Algorithm for Least-Squares Estimation of Nonlinear Parameters
Marquardt, D. W. (1963) · Journal of the Society for Industrial and Applied Mathematics · doi:10.1137/0111030 · Cited by 30,728
Effect of the damping function in dispersion corrected density functional theory
Grimme, S., Ehrlich, S., & Goerigk, L. (2011) · Journal of Computational Chemistry · doi:10.1002/jcc.21759 · Cited by 28,221
Self-citation
Cited by
Kühne, T. D., Iannuzzi, M., Del Ben, M., Rybkin, V. V., Seewald, P., Stein, F., Laino, T., Khaliullin, R. Z., Schütt, O., Schiffmann, F., et al. (2020) · The Journal of Chemical Physics · doi:10.1063/5.0007045 · Cited by 4,468
Towards the online computer-aided design of catalytic pockets
Falivene, L., Cao, Z., Petta, A., Serra, L., Poater, A., Oliva, R., Scarano, V., & Cavallo, L. (2019) · Nature Chemistry · doi:10.1038/s41557-019-0319-5 · Cited by 1,290
Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems
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CREST—A program for the exploration of low-energy molecular chemical space
Pracht, P., Grimme, S., Bannwarth, C., Bohle, F., Ehlert, S., Feldmann, G., Gorges, J., Müller, M., Neudecker, T., Plett, C., et al. (2024) · The Journal of Chemical Physics · doi:10.1063/5.0197592 · Cited by 574
Self-citationLeveraging large language models for predictive chemistry
Jablonka, K. M., Schwaller, P., Ortega-Guerrero, A., & Smit, B. (2024) · Nature Machine Intelligence · doi:10.1038/s42256-023-00788-1 · Cited by 378
Metadata
- Authors
- Bannwarth, C., Ehlert, S., & Grimme, S.
- Venue
- Journal of Chemical Theory and Computation
- Publisher
- American Chemical Society (ACS)
- Published
- 2019-02-11
- Volume
- 15
- Issue
- 3
- Pages
- 1652-1671
- ISSN
- 1549-9618 (ISSN-L)
- 1549-9626
- OpenAlex
- W2911997094
- Cited by
- 4,399
- References
- 3
- FWCI
- 117.00
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Bannwarth, C., Ehlert, S., & Grimme, S. (2019). GFN2-xTB—An Accurate and Broadly Parametrized Self-Consistent Tight-Binding Quantum Chemical Method with Multipole Electrostatics and Density-Dependent Dispersion Contributions. Journal of Chemical Theory and Computation. https://doi.org/10.1021/acs.jctc.8b01176
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