Investigating the effects of chemical composition of motor oils on their viscosity indices using gas chromatography and chemometrics techniques

Abstract

In this study, we focused on combination of gas chromatography and chemometrics techniques for relating the viscosity indices (VI) of motor oils to their chemical compositions. Partial least square (PLS) algorithm was used for relating the retention times of the collected chromatograms to VI of motor oils. The constructed model showed acceptable statistical values which indicate the robustness of the developed PLS model. GC-MS analysis was used for identification of the important chemicals affecting the values of VIs. Nonane, Pentafluoropropionic acid, Phthalic acid, nonylphenol and Tetracosane were suggested to have positive impacts on the values of VIs of motor oils.