Simple Linear Regression Models for Prediction of Ionization Energies, Electron Affinities, and Fundamental Gaps of Atoms and Molecules
Linear regression equations were developed for different density functionals using data from the CCCBDB, along with a test set of 89 ionization energies (IE) and 76 electron affinities (EA) so that experimental IE and EA can be predicted from orbital energies. Separate equations were determined for different classes of atoms and molecules. These relationships were also applied to all occupied orbitals to simulate the photoemission spectra of organic molecules with accuracy similar to that of other computational methods at a fraction of the cost. The error for large molecules (up to 200 atoms) can be below 0.2 eV with many functionals for the prediction of the IE and EA.
Authors
- Rebecca K. Carlson (ORCID: https://orcid.org/0000-0002-1710-5816)
Institutions
- National Institute of Standards and Technology (US)
- National Institute of Standards (EG)
- NOAA Chemical Sciences Laboratory (US)
Publication Details
- Journal
- Journal of Chemical Theory and Computation
- Published
- 2025-03-26
- DOI
- https://doi.org/10.1021/acs.jctc.4c01591
- Citations
- 1
- Primary Topic
- Mass Spectrometry Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.76