ωB97X-V: A 10-parameter, range-separated hybrid, generalized gradient approximation density functional with nonlocal correlation, designed by a survival-of-the-fittest strategy
Open accessAbstract
A 10-parameter, range-separated hybrid (RSH), generalized gradient approximation (GGA) density functional with nonlocal correlation (VV10) is presented. Instead of truncating the B97-type power series inhomogeneity correction factors (ICF) for the exchange, same-spin correlation, and opposite-spin correlation functionals uniformly, all 16,383 combinations of the linear parameters up to fourth order (m = 4) are considered. These functionals are individually fit to a training set and the resulting parameters are validated on a primary test set in order to identify the 3 optimal ICF expansions. Through this procedure, it is discovered that the functional that performs best on the training and primary test sets has 7 linear parameters, with 3 additional nonlinear parameters from range-separation and nonlocal correlation. The resulting density functional, ωB97X-V, is further assessed on a secondary test set, the parallel-displaced coronene dimer, as well as several geometry datasets. Furthermore, the basis set dependence and integration grid sensitivity of ωB97X-V are analyzed and documented in order to facilitate the use of the functional.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The ωB97X-D3(BJ) functional shows considerably better performance for water cluster binding energies and reaction barriers than the baseline SCAN+D3(BJ) functional.
“For the higher-level reference, we chose the range-separated hybrid DFT functional ωB97X complemented with the empirical dispersion correction D3(BJ): a functional that shows considerably better performance for water cluster binding energies and reaction barriers74,77,78 than our baseline reference SCAN+D3(BJ) functional.”
From A reactive neural network framework for water-loaded acidic zeolites (2024) · cites this paper as [77]
Cites
Generalized Gradient Approximation Made Simple
Perdew, J. P., Burke, K., & Ernzerhof, M. (1996) · Physical Review Letters · doi:10.1103/physrevlett.77.3865 · Cited by 215,824 · see citing works
Density-functional thermochemistry. III. The role of exact exchange
Becke, A. D. (1993) · The Journal of Chemical Physics · doi:10.1063/1.464913 · Cited by 103,767 · see citing works
Self-interaction correction to density-functional approximations for many-electron systems
Perdew, J. P., & Zunger, A. (1981) · Physical Review B · doi:10.1103/physrevb.23.5048 · Cited by 20,887 · see citing works
Self-consistent molecular orbital methods. XX. A basis set for correlated wave functions
Krishnan, R., Binkley, J. S., Seeger, R., & Pople, J. A. (1980) · The Journal of Chemical Physics · doi:10.1063/1.438955 · Cited by 17,772 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Mardirossian, N., & Head-Gordon, M. (2017) · Molecular Physics · doi:10.1080/00268976.2017.1333644 · Cited by 2,307 · see citing works
Self-citationNandy, A., Duan, C., Taylor, M. G., Liu, F., Steeves, A. H., & Kulik, H. J. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00347 · Cited by 358 · see citing works
Brauer, B., Kesharwani, M. K., Kozuch, S., & Martin, J. M. L. (2016) · Physical Chemistry Chemical Physics · doi:10.1039/c6cp00688d · Cited by 238 · see citing works
A reactive neural network framework for water-loaded acidic zeolites
Erlebach, A., Šípka, M., Saha, I., Nachtigall, P., Heard, C. J., & Grajciar, L. (2024) · Nature Communications · doi:10.1038/s41467-024-48609-2 · Cited by 47 · see citing works
“…we chose the range-separated hybrid DFT functional ω B97X complemented with the empirical dispersion correction D3(BJ): a functional that shows considerably better performance for water cluster binding energies and reaction barriers 74,77,78 than our baseline reference SCAN+D3(BJ) functional.”
MethodCO <sub>2</sub> on Graphene: Benchmarking Computational Approaches to Noncovalent Interactions
Ehlert, C., Piras, A., & Gryn’ova, G. (2023) · ACS Omega · doi:10.1021/acsomega.3c03251 · Cited by 15 · see citing works
- Authors
- Mardirossian, N., & Head-Gordon, M.
- Affiliations
- Lawrence Berkeley National Laboratory (US)
- ORCID
- Mardirossian, Narbe
- Venue
- Physical Chemistry Chemical Physics
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2014
- Volume
- 16
- Issue
- 21
- Pages
- 9904
- ISSN
- 1463-9076 (ISSN-L)
- 1463-9084
- OpenAlex
- W2099190231
- Cited by
- 986
- References
- 4
- Citations by year
- 2026: 129 · 2025: 115 · 2024: 126 · 2023: 136 · 2022: 102 · 2021: 95 · 2020: 83 · 2019: 57 · 2018: 37 · 2017: 28 · 2016: 38 · 2015: 23 · 2014: 16
- FWCI
- 13.22
- Type
- journal article
- Language
- en
- Open access
- green
- www.osti.gov
- Locations
- Physical Chemistry Chemical Physics (publishedVersion)
- PubMed (publishedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Topics
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Advanced Chemical Physics Studies
- Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
- Physical Sciences › Chemistry › Organic Chemistry › Chemical Reaction Mechanisms
- Keywords
- generalized gradient approximation, nonlocal correlations, basis set effects, geometry optimization
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review