NDLI: Improving the Accuracy of Density Functional Theory (DFT) Calculation for Homolysis Bond Dissociation Energies of Y-NO Bond: Generalized Regression Neural Network Based on Grey Relational Analysis and Principal Component Analysis

Content Provider	PubMed Central
Author	Li, Hong Zhi Tao, Wei Gao, Ting Li, Hui Lu, Ying Hua Su, Zhong Min
Copyright Year	2011
Abstract	We propose a generalized regression neural network (GRNN) approach based on grey relational analysis (GRA) and principal component analysis (PCA) (GP-GRNN) to improve the accuracy of density functional theory (DFT) calculation for homolysis bond dissociation energies (BDE) of Y-NO bond. As a demonstration, this combined quantum chemistry calculation with the GP-GRNN approach has been applied to evaluate the homolysis BDE of 92 Y-NO organic molecules. The results show that the ull-descriptor GRNN without GRA and PCA (F-GRNN) and with GRA (G-GRNN) approaches reduce the root-mean-square (RMS) of the calculated homolysis BDE of 92 organic molecules from 5.31 to 0.49 and 0.39 kcal mol−1 for the B3LYP/6-31G (d) calculation. Then the newly developed GP-GRNN approach further reduces the RMS to 0.31 kcal mol−1. Thus, the GP-GRNN correction on top of B3LYP/6-31G (d) can improve the accuracy of calculating the homolysis BDE in quantum chemistry and can predict homolysis BDE which cannot be obtained experimentally.
Related Links	http://dx.doi.org/10.3390/ijms12042242
Ending Page	2261
Page Count	20
Starting Page	2242
File Format	PDF
ISSN	14220067
e-ISSN	14220067
Journal	International Journal of Molecular Sciences
Issue Number	4
Volume Number	12
Language	English
Publisher	Molecular Diversity Preservation International (MDPI)
Publisher Date	2011-04-01
Access Restriction	Open
Rights Holder	Molecular Diversity Preservation International (MDPI)
Subject Keyword	Physical and Theoretical Chemistry Inorganic Chemistry Organic Chemistry Spectroscopy Molecular Biology Catalysis Computer Science Applications Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Spectroscopy Organic Chemistry Medicine Molecular Biology Physical and Theoretical Chemistry Catalysis Inorganic Chemistry Computer Science Applications

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