Table of Contents
Journal of Theoretical Chemistry
Volume 2014, Article ID 520652, 6 pages
http://dx.doi.org/10.1155/2014/520652
Research Article

QSPR Models for Octane Number Prediction

1Chemistry Department, Faculty of Applied Science, Umm Al-Qura University, Makah, Saudi Arabia
2Petrochemicals Department, Egyptian Petroleum Research Institute, Nasr City, Cairo 11727, Egypt

Received 31 March 2014; Accepted 7 June 2014; Published 19 August 2014

Academic Editor: D. Sajan

Copyright © 2014 Jabir H. Al-Fahemi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Quantitative structure-property relationship (QSPR) is performed as a means to predict octane number of hydrocarbons via correlating properties to parameters calculated from molecular structure; such parameters are molecular mass , hydration energy , boiling point , octanol/water distribution coefficient , molar refractivity , critical pressure , critical volume , and critical temperature . Principal component analysis (PCA) and multiple linear regression technique (MLR) were performed to examine the relationship between multiple variables of the above parameters and the octane number of hydrocarbons. The results of PCA explain the interrelationships between octane number and different variables. Correlation coefficients were calculated using M.S. Excel to examine the relationship between multiple variables of the above parameters and the octane number of hydrocarbons. The data set was split into training of 40 hydrocarbons and validation set of 25 hydrocarbons. The linear relationship between the selected descriptors and the octane number has coefficient of determination , statistical significance , and standard errors . The obtained QSPR model was applied on the validation set of octane number for hydrocarbons giving and .