title: Application of a quantitative structure retention relationship approach for the prediction of the two-dimensional gas chromatography retention times of polycyclic aromatic sulfur heterocycle compounds.
abstract: Information on the sulfur classes present in petroleum is a key factor in determining the value of refined products and processing behavior in the refinery. A large part of the sulfur present is included in polycyclic aromatic sulfur heterocycles (PASHs), which in turn are difficult to desulfurize. Furthermore, some PASHs are potentially more mutagenic and carcinogenic than polycyclic aromatic hydrocarbons, PAHs. All of this calls for improved methods for the identification and quantification of individual sulfur species. Recent advances in analytical techniques such as comprehensive two-dimensional gas chromatography (GC×GC) have enabled the identification of many individual sulfur species. However, full identification of individual components, particularly in virgin oil fractions, is still out of reach as standards for numerous compounds are unavailable. In this work, a method for accurately predicting retention times in GC×GC using a QSRR (quantitative structure retention relationship) method was very helpful for the identification of individual sulfur compounds. Retention times for 89 saturated, aromatic, and polyaromatic sulfur-containing heterocyclic compounds were determined using two-dimensional gas chromatography. These retention data were correlated with molecular descriptors generated with CODESSA software. Two independent QSRR relationships were derived for the primary as well as the secondary retention characteristics. The predictive ability of the relationships was tested by using both independent sets of compounds and a cross-validation technique. When the corresponding chemical standards are unavailable, the equations developed for predicting retention times can be used to identify unknown chromatographic peaks by matching their retention times with those of sulfur compounds of known molecular structure.
authors.affiliation: CanmetENERGY, Natural Resources Canada, 1 Oil Patch Drive, Devon, Alberta T9G 1A8, Canada. Electronic address: rafal.gieleciak@canada.ca.
authors.forename: Rafal
authors.initials: R
authors.lastname: Gieleciak
authors.affiliation: CanmetENERGY, Natural Resources Canada, 1 Oil Patch Drive, Devon, Alberta T9G 1A8, Canada.
authors.forename: Darcy
authors.initials: D
authors.lastname: Hager
authors.affiliation: CanmetENERGY, Natural Resources Canada, 1 Oil Patch Drive, Devon, Alberta T9G 1A8, Canada.
authors.forename: Nicole E
authors.initials: NE
authors.lastname: Heshka
mesh_terms: D002623:Chemistry Techniques, Analytical / Q000379:methods*; D002849:Chromatography, Gas; D006571:Heterocyclic Compounds / Q000032:analysis / Q000737:chemistry; D015394:Molecular Structure; D010578:Petroleum / Q000032:analysis*; D011084:Polycyclic Aromatic Hydrocarbons / Q000032:analysis*; D013455:Sulfur / Q000737:chemistry*; D013457:Sulfur Compounds / Q000032:analysis
chemical_list: D006571:Heterocyclic Compounds; D010578:Petroleum; D011084:Polycyclic Aromatic Hydrocarbons; D013457:Sulfur Compounds; D013455:Sulfur
keywords: PASHs; Quantitative structure retention relationship (QSRR); Retention prediction; Sulfur standards; Two dimensional gas chromatography (GC×GC); Variable selection