Accurate Quantum Chemical Calculation of Ionization Potentials: Validation of the DFT-LOC Approach via a Large Data Set Obtained from Experiments and Benchmark Quantum Chemical Calculations.

Autor: Li G; Department of Chemistry, Columbia University, New York, New York 10027, United States., Rudshteyn B; Department of Chemistry, Columbia University, New York, New York 10027, United States., Shee J; Department of Chemistry, Columbia University, New York, New York 10027, United States., Weber JL; Department of Chemistry, Columbia University, New York, New York 10027, United States., Coskun D; Department of Chemistry, Columbia University, New York, New York 10027, United States., Bochevarov AD; Schrödinger, Inc., New York, New York 10036, United States., Friesner RA; Department of Chemistry, Columbia University, New York, New York 10027, United States.
Jazyk: angličtina
Zdroj: Journal of chemical theory and computation [J Chem Theory Comput] 2020 Apr 14; Vol. 16 (4), pp. 2109-2123. Date of Electronic Publication: 2020 Mar 20.
DOI: 10.1021/acs.jctc.9b00875
Abstrakt: Density functional theory (DFT) is known to often fail when calculating thermodynamic values, such as ionization potentials (IPs), due to nondynamical error (i.e., the self-interaction term). Localized orbital corrections (LOCs), derived from assigning corresponding corrections for the atomic orbitals, bonds, and paired and unpaired electrons, are utilized to correct the IPs calculated from DFT. Some of the assigned parameters, which are physically due to the contraction of and change of the environment around a bond, depend on identifying the location in the molecule from which the electron is removed using differences in the charge density between neutral and oxidized species. In our training set, various small organic and inorganic molecules from the literature with the reported experimental IP were collected using the NIST database. For certain molecules with uncertain or no experimental measurements, we obtain the IP using coupled cluster theory and auxiliary field quantum Monte Carlo. After applying these corrections, as generated by least-squares regression, LOC reduces the mean absolute deviation (MAD) of the training set from 0.143 to 0.046 eV ( R 2 = 0.895), and LOC reduces the MAD of the test set from 0.192 to 0.097 eV ( R 2 = 0.833).
Databáze: MEDLINE