QSPR Models for Octane Number Prediction

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 M , hydration energy E H , boiling point B P , octanol/water distribution coefficient log P , molar refractivity M R , critical pressure C P , critical volume C V , and critical temperature C T . 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 ( R 2 = 0.932 ) , statistical significance ( F = 53.21 ) , and standard errors ( s   = 7.7 ) . The obtained QSPR model was applied on the validation set of octane number for hydrocarbons giving R C V 2 = 0.942 and s = 6.328 .