QSPR Models for Octane Number Prediction. (18th August 2014)

• Record Type: Journal Article
• Authors: Al-Fahemi, Jabir H.; Albis, Nahla A.; Gad, Elshafie A. M.
• Other Names: Sajan D. Academic Editor.
• Is Part Of: Journal of theoretical chemistry. Volume 2014(2014)
• Publication Date: 2014-08-18
• Subjects: Chemistry, Physical and theoretical -- Periodicals; Chemistry, Physical and theoretical; Periodicals; Electronic journals; 541.2
• DOI: 10.1155/2014/520652
• Languages: English
• ISSNs: 2356-7686

Abstract

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 massM, hydration energyE H, boiling pointB P, octanol/water distribution coefficientlog P, molar refractivityM R, critical pressureC P, critical volumeC V, and critical temperatureC 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 givingR C V 2 = 0.942 ands = 6.328 .