Comprehensive Two-Dimensional High-Speed Gas Chromatography with Chemometric Analysis

High-speed comprehensive two-dimensional gas chromatography (GC×GC) is performed, in which a polar second column performs separations every half second on portions of the effluent from a nonpolar first column. Chemometric techniques that are traditionally used on chromatographic separations with mul...

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Veröffentlicht in:Analytical chemistry (Washington) 1998-07, Vol.70 (14), p.2796-2804
Hauptverfasser: Bruckner, Carsten A, Prazen, Bryan J, Synovec, Robert E
Format: Artikel
Sprache:eng
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Zusammenfassung:High-speed comprehensive two-dimensional gas chromatography (GC×GC) is performed, in which a polar second column performs separations every half second on portions of the effluent from a nonpolar first column. Chemometric techniques that are traditionally used on chromatographic separations with multichannel detection are applied to two-dimensional chromatographic data, for the purpose of quantifying incompletely resolved peaks. Generalized rank annihilation method (GRAM) is evaluated in the quantification of varying amounts of selected overlapped analytes in a GC×GC analysis of modified white gasoline. GRAM requires a sample and standard data set for quantification, and the high retention time precision arising from use of shortened GC columns aids in the analysis. Results from GRAM analysis of GC×GC data are compared with a reference GC method. The test analytes ethylbenzene and m-xylene, existing in various proportions in white gasoline samples, were successfully deconvoluted despite having resolutions of 0.46 and 0.20 on the first and second dimensions of separation, respectively. Like other second-order techniques, GRAM was able to reliably quantify m-xylene despite the presence in the analytical sample of an overlapping compound not present in the calibration standard. Because GRAM can be successfully applied to GC×GC data, full resolution of all the analytes of interest is not necessary. As a result, GC×GC run times can be dramatically shortened, which has significant implications for analyses in which short cycle times are critical, such as in process analysis.
ISSN:0003-2700
1520-6882
DOI:10.1021/ac980164m