4.7 Article

A localized orbital analysis of the thermochemical errors in hybrid density functional theory: Achieving chemical accuracy via a simple empirical correction scheme

Journal

JOURNAL OF CHEMICAL PHYSICS
Volume 125, Issue 12, Pages -

Publisher

AIP Publishing
DOI: 10.1063/1.2263795

Keywords

-

Funding

  1. NIGMS NIH HHS [GM 40526] Funding Source: Medline

Ask authors/readers for more resources

This paper describes an empirical localized orbital correction model which improves the accuracy of density functional theory (DFT) methods for the prediction of thermochemical properties for molecules of first and second row elements. The B3LYP localized orbital correction version of the model improves B3LYP DFT atomization energy calculations on the G3 data set of 222 molecules from a mean absolute deviation (MAD) from experiment of 4.8 to 0.8 kcal/mol. The almost complete elimination of large outliers and the substantial reduction in MAD yield overall results comparable to the G3 wave-function-based method; furthermore, the new model has zero additional computational cost beyond standard DFT calculations. The following four classes of correction parameters are applied to a molecule based on standard valence bond assignments: corrections to atoms, corrections to individual bonds, corrections for neighboring bonds of a given bond, and radical environmental corrections. Although the model is heuristic and is based on a 22 parameter multiple linear regression to experimental errors, each of the parameters is justified on physical grounds, and each provides insight into the fundamental limitations of DFT, most importantly the failure of current DFT methods to accurately account for nondynamical electron correlation. (c) 2006 American Institute of Physics.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available