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Kiralj R, Ferreira MM. Predicting bond lengths in planar benzenoid polycyclic aromatic hydrocarbons: a chemometric approach. J Chem Inf Comput Sci. 2002;42(3):508-23doi: 10.1021/ci010063g.
Kiralj, R., & Ferreira, M. M. (2002). Predicting bond lengths in planar benzenoid polycyclic aromatic hydrocarbons: a chemometric approach. Journal of chemical information and computer sciences, 42(3), 508-23. https://doi.org/10.1021/ci010063g
Kiralj, R, and Ferreira, M M C. "Predicting bond lengths in planar benzenoid polycyclic aromatic hydrocarbons: a chemometric approach." Journal of chemical information and computer sciences vol. 42,3 (2002): 508-23. doi: https://doi.org/10.1021/ci010063g
Kiralj R, Ferreira MM. Predicting bond lengths in planar benzenoid polycyclic aromatic hydrocarbons: a chemometric approach. J Chem Inf Comput Sci. 2002 May-Jun;42(3):508-23. doi: 10.1021/ci010063g. PMID: 12086508.
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J Chem Inf Comput Sci. 2002 May-Jun;42(3):508-23. doi: 10.1021/ci010063g.

Predicting bond lengths in planar benzenoid polycyclic aromatic hydrocarbons: a chemometric approach.

Journal of chemical information and computer sciences

R Kiralj, M M C Ferreira

Affiliations

  1. Laboratório de Quimiometria Teórica e Aplicada, Instituto de Química, Universidade Estadual de Campinas, Campinas, SP, 13083-970, Brazil. [email protected]

PMID: 12086508 DOI: 10.1021/ci010063g

Abstract

Two hundred and twenty-three aromatic carbon-carbon bond lengths in high precision crystal structures containing 22 planar condensed benzenoid polycyclic aromatic hydrocarbons (PB-PAHs) were related to the Pauling pi-bond order, its analogue corrected to crystal packing effects, the number of hexagonal rings around the bond, and the numbers of carbons atoms around the bond at topological distance one and two. Principal Component Analysis (PCA) showed that the bond lengths in PB-PAHs are at least two-dimensional phenomenon, with well pronounced classification into 12 types of bonds, as confirmed with Hierachical Cluster Analysis (HCA). Consequently, Multiple Linear Regression (MLR) and Partial Least Squares (PLS) models were superior to univariate models, reducing the degeneration of the data set and improving the estimation of Julg's structural aromaticity index. The approximate regression models based on topological descriptors only were built for fast and easy prediction of bond lengths and bond orders in PB-PAHs.

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