Abstract
IR and NIR spectra were correlated to Hildebrand and Hansen solubility parameters through use of multivariate data analysis. PLS‐1 models were developed and used to predict solubility parameters for solvents, crude oils, and SARA fractions. PLS regression showed potential for good correlation of the solubility parameters with IR and NIR spectra. Principal component analysis of IR spectra showed that crude oils are grouped according to their relative contents of heavy components such as asphaltenes. PCA of IR spectra for SARA fractions resulted in obvious groupings of the respective fractions. Prediction of solubility parameters from IR spectra of polymers, crude oils, and SARA fractions gave values that are comparable to literature values. This study indicates that correlation of solubility parameters with IR and NIR spectra is possible. In turn, it may be possible to develop models that can predict the polarities of crude oils and crude oil fractions such as resins and asphaltenes.
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