The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Ionization Potential, Electron Affinity, Electronegativity, Hardness, and Electron Excitation Energy: Molecular Properties from Density Functional Theory Orbital Energies
Abstract
Representative atomic and molecular systems, including various inorganic and organic molecules with covalent and ionic bonds, have been studied by using density functional theory. The calculations were done with the commonly used exchange-correlation functional B3LYP followed by a comprehensive analysis of the calculated highest-occupied and lowest-unoccupied Kohn−Sham orbital (HOMO and LUMO) energies. The basis set dependence of the DFT results shows that the economical 6-31+G* basis set is generally sufficient for calculating the HOMO and LUMO energies (if the calculated LUMO energies are negative) for use in correlating with molecular properties. The directly calculated ionization potential (IP), electron affinity (EA), electronegativity (χ), hardness (η), and first electron excitation energy (τ) are all in good agreement with the available experimental data. A generally applicable linear correlation relationship exists between the calculated HOMO energies and the experimental/calculated IPs. We have also found satisfactory linear correlation relationships between the calculated LUMO energies and experimental/calculated EAs (for the bound anionic states), between the calculated average HOMO/LUMO energies and χ values, between the calculated HOMO−LUMO energy gaps and η values, and between the calculated HOMO−LUMO energy gaps and experimental/calculated first excitation energies. By using these linear correlation relationships, the calculated HOMO and LUMO energies can be employed to semiquantitatively estimate ionization potential, electron affinity, electronegativity, hardness, and first excitation energy.
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
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
Pearson, R. G. (1963) · Journal of the American Chemical Society · doi:10.1021/ja00905a001 · Cited by 10,475
Cited by
A Review of Electrocatalytic Reduction of Dinitrogen to Ammonia under Ambient Conditions
Cui, X., Tang, C., & Zhang, Q. (2018) · Advanced Energy Materials · doi:10.1002/aenm.201800369 · Cited by 1,314
Comparison of DFT Methods for Molecular Orbital Eigenvalue Calculations
Zhang, G., & Musgrave, C. B. (2007) · The Journal of Physical Chemistry A · doi:10.1021/jp061633o · Cited by 911
Yang, J., Guo, Y., Jiang, R., Qin, F., Zhang, H., Lu, W., Wang, J., & Yu, J. C. (2018) · Journal of the American Chemical Society · doi:10.1021/jacs.8b03537 · Cited by 499
Solar-Energy-Mediated Methane Conversion
Song, H., Meng, X., Wang, Z.-J., Liu, H., & Ye, J. (2019) · Joule · doi:10.1016/j.joule.2019.06.023 · Cited by 478
Fundamental Gaps in Finite Systems from Eigenvalues of a Generalized Kohn-Sham Method
Stein, T., Eisenberg, H., Kronik, L., & Baer, R. (2010) · Physical Review Letters · doi:10.1103/physrevlett.105.266802 · Cited by 469
Theoretical study of ionization and one‐electron oxidation potentials of N‐heterocyclic compounds
Sviatenko, L. K., Gorb, L., Hill, F. C., & Leszczynski, J. (2013) · Journal of Computational Chemistry · doi:10.1002/jcc.23228 · Cited by 295
MISATO: machine learning dataset of protein–ligand complexes for structure-based drug discovery
Siebenmorgen, T., Menezes, F., Benassou, S., Merdivan, E., Didi, K., Mourão, A. S. D., Kitel, R., Liò, P., Kesselheim, S., Piraud, M., et al. (2024) · Nature Computational Science · doi:10.1038/s43588-024-00627-2 · Cited by 75
Paul, N., Harish, G., & Banerjee, T. (2023) · ACS Sustainable Chemistry & Engineering · doi:10.1021/acssuschemeng.2c06137 · Cited by 51
Roymuhury, S. K., Chakraborty, D., & Ramkumar, V. (2015) · Dalton Transactions · doi:10.1039/c5dt01092f · Cited by 34
MISATO - Machine learning dataset of protein-ligand complexes for structure-based drug discovery
(2023) · doi:10.1101/2023.05.24.542082 · Cited by 18
Metadata
- Authors
- Zhan, C.-G., Nichols, J. A., & Dixon, D. A.
- Venue
- The Journal of Physical Chemistry A
- Publisher
- American Chemical Society (ACS)
- Published
- 2003-04-26
- Volume
- 107
- Issue
- 20
- Pages
- 4184-4195
- ISSN
- 1089-5639 (ISSN-L)
- 1520-5215
- OpenAlex
- W2031240265
- Cited by
- 1,555
- References
- 3
- FWCI
- 10.33
- Type
- journal article
- Language
- en
- Open access
- closed
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.