Simple, non-moving modulation interface for comprehensive two-dimensional gas chromatography

Department of Analytical Chemistry and Applied Spectroscopy, Vrije Universiteit, De Boelelaan 1083, 1081 HV Amsterdam, Netherlands
Journal of Chromatography A (Impact Factor: 4.26). 07/2001; DOI: 10.1016/S0021-9673(01)00785-3

ABSTRACT A simple, non-moving dual-stage CO2 jet modulator is described, which cools two short sections of the front end of the second-dimension column of a comprehensive two-dimensional gas chromatograph. A stream of expanding CO2 is sprayed directly onto this capillary column to trap small fractions eluting from the first-dimension column. Remobilization of the trapped analytes is performed by direct heating by the GC oven air. Installation, maintenance and control of the modulator is simple. Focusing and remobilization of the fractions is a very efficient process, as the bandwidths of the re-injected pulses are less than 10 ms. As a result, alkane peaks eluting from the second-dimension column have peakwidths at the baseline of only 120 ms.

  • [Show abstract] [Hide abstract]
    ABSTRACT: A high-speed gas chromatography system, the gas chromatographic sensor (GCS), is developed and evaluated. The GCS combines fast separations and chemometric analysis to produce an instrument capable of high-speed, high-throughput screening and quantitative analysis of complex chemical mixtures on a similar time scale as typical chemical sensors. The GCS was evaluated with 28 test mixtures consisting of 15 compounds from four chemical classes: alkanes, ketones, alkyl benzenes, and alcohols. The chromatograms are on the order of one second in duration, which is considerably faster than the traditional use of gas chromatography. While complete chromatographic separation of each analyte peak is not aimed for, chemical information is readily extracted through chemometric data analysis and quantification of the samples is achieved in considerably less time than conventional gas chromatography.Calibration models to predict percent volume content of either alkanes or ketones were constructed using partial least squares (PLS) regression on calibration sets consisting of the five replicate GCS runs of six different samples. The percent volume content of the alkane and ketone chemical classes were predicted on five replicate runs of the 22 remaining samples ranging from 0 to 50 or 60% depending on the class. Root mean square errors of prediction were 2–3% relative to the mean percent volume values for either alkane or ketone prediction models, depending on the samples chosen for the calibration set of that model. The alkyl benzenes and alcohols present in the calibration sets or samples were treated as variable background interference. It is anticipated that the GCS will eventually be used to rapidly sample and directly analyze industrial processes or for the high throughput analysis of batches of samples.
    Analytica Chimica Acta 08/2003; 490(1). · 4.52 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Comprehensive two-dimensional gas chromatography (GCxGC) is a new technology for chemical separation. In GCxGC analysis, chemical identification is a critical task that can be performed by peak pattern matching. Peak pattern matching tries to identify the chemicals by establishing correspondences from the known peaks in a peak template to the unknown peaks in a target peak pattern. After the correspondences are established, information carried by known peaks are copied into the unknown peaks. The peaks in the target peak pattern are then identified. Using peak locations as the matching features, peak patterns can be represented as point patterns and the peak pattern matching problem becomes a point pattern matching problem. In GCxGC, the chemical separation process imposes an ordering constraint on peak retention time (peak location). Based on the ordering constraint, the matching technique proposed in this paper forms directed edge patterns from point patterns and then matches the point patterns by matching the edge patterns. Preliminary experiments on GCxGC peak patterns suggest that matching the edge patterns is much more efficient than matching the corresponding point patterns.
    Proc SPIE 09/2004;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Comprehensive two-dimensional (2D) gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS) is a highly capable instrumental platform that produces complex and information-rich multi-dimensional chemical data. The data can be initially overwhelming, especially when many samples (of various sample classes) are analyzed with multiple injections for each sample. Thus, the data must be analyzed in such a way as to extract the most meaningful information. The pixel-based and peak table-based Fisher ratio algorithmic approaches have been used successfully in the past to reduce the multi-dimensional data down to those chemical compounds that are changing between the sample classes relative to those that are not changing (i.e., chemical feature selection). We report on the initial development of a computationally fast novel tile-based Fisher-ratio software that addresses the challenges due to 2D retention time misalignment without explicitly aligning the data, which is often a shortcoming for both pixel-based and peak table-based algorithmic approaches. Concurrently, the tile-based Fisher-ratio algorithm significantly improves the sensitivity contrast of true positives against a background of potential false positives and noise. In this study, eight compounds, plus one internal standard, were spiked into diesel at various concentrations. The tile-based F-ratio algorithmic approach was able to "discover" all spiked analytes, within the complex diesel sample matrix with thousands of potential false positives, in each possible concentration comparison, even at the lowest absolute spiked analyte concentration ratio of 1.06, the ratio between the concentrations in the spiked diesel sample to the native concentration in diesel.
    Talanta 10/2013; 115:887-95. · 3.50 Impact Factor

Full-text (2 Sources)

Available from
Jul 4, 2014