The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Charge Model 5: An Extension of Hirshfeld Population Analysis for the Accurate Description of Molecular Interactions in Gaseous and Condensed Phases
Open accessAbstract
We propose a novel approach to deriving partial atomic charges from population analysis. The new model, called Charge Model 5 (CM5), yields class IV partial atomic charges by mapping from those obtained by Hirshfeld population analysis of density functional electronic charge distributions. The CM5 model utilizes a single set of parameters derived by fitting to reference values of the gas-phase dipole moments of 614 molecular structures. An additional test set (not included in the CM5 parametrization) contained 107 singly charged ions with nonzero dipole moments, calculated from the accurate electronic charge density, with respect to the center of nuclear charges. The CM5 model is applicable to any charged or uncharged molecule composed of any element of the periodic table in the gas phase or in solution. The CM5 model predicts dipole moments for the tested molecules that are more accurate on average than those from the original Hirshfeld method or from many other popular schemes including atomic polar tensor and Löwdin, Mulliken, and natural population analyses. In addition, the CM5 charge model is essentially independent of a basis set. It can be used with larger basis sets, and thereby this model significantly improves on our previous charge models CMx (x = 1-4 or 4M) and other methods that are prone to basis set sensitivity. CM5 partial atomic charges are less conformationally dependent than those derived from electrostatic potentials. The CM5 model does not suffer from ill conditioning for buried atoms in larger molecules, as electrostatic fitting schemes sometimes do. The CM5 model can be used with any level of electronic structure theory (Hartree-Fock, post-Hartree-Fock, and other wave function correlated methods or density functional theory) as long as an accurate electronic charge distribution and a Hirshfeld analysis can be computed for that level of theory.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
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
Lee, C., Yang, W., & Parr, R. G. (1988) · Physical Review B · doi:10.1103/physrevb.37.785 · Cited by 100,874
CRC Handbook of Chemistry and Physics
(2014) · doi:10.1201/b17118 · Cited by 57,706
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
Density-Functional Theory for Time-Dependent Systems
Runge, E., & Gross, E. K. U. (1984) · Physical Review Letters · doi:10.1103/physrevlett.52.997 · Cited by 8,914
Minimally augmented Karlsruhe basis sets
Zheng, J., Xu, X., & Truhlar, D. G. (2011) · Theoretical Chemistry Accounts · doi:10.1007/s00214-010-0846-z · Cited by 1,067
Self-citation
Cited by
LigParGen web server: an automatic OPLS-AA parameter generator for organic ligands
Dodda, L. S., Cabeza de Vaca, I., Tirado-Rives, J., & Jorgensen, W. L. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx312 · Cited by 1,746
Rosen, A. S., Iyer, S. M., Ray, D., Yao, Z., Aspuru-Guzik, A., Gagliardi, L., Notestein, J. M., & Snurr, R. Q. (2021) · Matter · doi:10.1016/j.matt.2021.02.015 · Cited by 538
Computational Approach to Molecular Catalysis by 3d Transition Metals: Challenges and Opportunities
Vogiatzis, K. D., Polynski, M. V., Kirkland, J. K., Townsend, J., Hashemi, A., Liu, C., & Pidko, E. A. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00361 · Cited by 423
Quantum-Chemical Characterization of the Properties and Reactivities of Metal–Organic Frameworks
Odoh, S. O., Cramer, C. J., Truhlar, D. G., & Gagliardi, L. (2015) · Chemical Reviews · doi:10.1021/cr500551h · Cited by 306
Self-citationClassical Electrostatics for Biomolecular Simulations
Cisneros, G. A., Karttunen, M., Ren, P., & Sagui, C. (2014) · Chemical Reviews · doi:10.1021/cr300461d · Cited by 259
Miranda, M. O., DePorre, Y., Vazquez-Lima, H., Johnson, M. A., Marell, D. J., Cramer, C. J., & Tolman, W. B. (2013) · Inorganic Chemistry · doi:10.1021/ic402255m · Cited by 79
Self-citationMarlier, E. E., Macaranas, J. A., Marell, D. J., Dunbar, C. R., Johnson, M. A., DePorre, Y., Miranda, M. O., Neisen, B. D., Cramer, C. J., Hillmyer, M. A., et al. (2016) · ACS Catalysis · doi:10.1021/acscatal.5b02607 · Cited by 60
Self-citationFrom QM/MM to ML/MM: A new era in multiscale modeling
Grassano, J. S., Pickering, I., Roitberg, A. E., Estrin, D. A., & Semelak, J. A. (2025) · Chemical Physics Reviews · doi:10.1063/5.0260078 · Cited by 20
Metadata
- Authors
- Marenich, A. V., Jerome, S. V., Cramer, C. J., & Truhlar, D. G.
- Venue
- Journal of Chemical Theory and Computation
- Publisher
- American Chemical Society (ACS)
- Published
- 2012-02-03
- Volume
- 8
- Issue
- 2
- Pages
- 527-541
- ISSN
- 1549-9618 (ISSN-L)
- 1549-9626
- OpenAlex
- W2323403662
- Cited by
- 1,030
- References
- 6
- FWCI
- 13.46
- Type
- journal article
- Language
- en
- Open access
- hybrid
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
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.