The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Efficient and accurate expansion methods for molecules in local density models
Open accessAbstract
The effects of truncation of the effective Hamiltonian of local density theory through shape approximations to the molecular charge density are examined. A self-consistent multicenter-multipolar (SCM) representation of the density is introduced, which allows calculation of the Coulomb and exchange-correlation potentials to any desired level of precision. The related question of quality of wave function expansion bases required to reproduce spectra and densities with chemical accuracy is explored. The efficiency and accuracy of the SCM approach are verified by applications to O2 and CO; results are given for the metal cluster compound Ru3(CO)12.
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Citations
Cites
Self-Consistent Equations Including Exchange and Correlation Effects
Kohn, W., & Sham, L. J. (1965) · Physical Review · doi:10.1103/physrev.140.a1133 · Cited by 64,135
Cited by
te Velde, G., Bickelhaupt, F. M., Baerends, E. J., Fonseca Guerra, C., van Gisbergen, S. J. A., Snijders, J. G., & Ziegler, T. (2001) · Journal of Computational Chemistry · doi:10.1002/jcc.1056 · Cited by 10,152
Metadata
- Authors
- Delley, B., & Ellis, D. E.
- Venue
- The Journal of Chemical Physics
- Publisher
- AIP Publishing
- Published
- 1982-02-15
- Volume
- 76
- Issue
- 4
- Pages
- 1949-1960
- ISSN
- 0021-9606 (ISSN-L)
- 1089-7690
- OpenAlex
- W2088177744
- Cited by
- 434
- References
- 1
- FWCI
- 10.83
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Delley, B., & Ellis, D. E. (1982). Efficient and accurate expansion methods for molecules in local density models. The Journal of Chemical Physics. https://doi.org/10.1063/1.443168
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.
