Linear regression correction to first principle theoretical calculations - Improved descriptors and enlarged training set

Xue Mei Duan, Zhen Hua Li, Hai Rong Hu, Guo Liang Song, Wen Ning Wang, Guan Hua Chen, Kang Nian Fan

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

The linear regression correction previously developed to reduce quantum chemical calculation errors [X.M. Duan, G.L. Song, Z.H. Li, X.J. Wang, G.H. Chen, K.N. Fan, J. Chem. Phys. 121 (2004) 7086] has been further improved by using new descriptors obtained from natural bond orbital analysis and an enlarged training set of 350 organic, inorganic molecules and radicals. The new scheme is better suited for correcting reaction barriers. Upon linear regression correction, the mean absolute deviation for the new set decreases from 284.1, 8.2, 12.4 kcal/mol to 7.3, 3.3, 2.7 kcal/mol for the HF/6-31G(d), B3LYP/6-31G(d), and B3LYP/6-311G(2d,d,p) methods, respectively, and the mean absolute deviation of 12 barrier heights for six hydrogen transfer reactions is reduced from 5.3 to 2.9 kcal/mol for the B3LYP/6-311G(2d,d,p) method.

Original languageEnglish (US)
Pages (from-to)315-321
Number of pages7
JournalChemical Physics Letters
Volume409
Issue number4-6
DOIs
StatePublished - Jun 30 2005

Bibliographical note

Funding Information:
This work was supported by the National Natural Science Foundation of China Grant Nos. (20273015 and 20433030) and the Natural Science Foundation of Shanghai Science and Technology Committee Grant No. (02DJ14023).

Fingerprint

Dive into the research topics of 'Linear regression correction to first principle theoretical calculations - Improved descriptors and enlarged training set'. Together they form a unique fingerprint.

Cite this