Comprehensive two-dimensional (2D) gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS) is a versatile instrumental platform capable of collecting highly informative, yet highly complex, chemical data for a variety of samples. Fisher-ratio (F-ratio) analysis applied to the supervised comparison of sample classes algorithmically reduces complex GC × GC-TOFMS data sets to find class distinguishing chemical features. F-ratio analysis, using a tile-based algorithm, significantly reduces the adverse effects of chromatographic misalignment and spurious covariance of the detected signal, enhancing the discovery of true positives while simultaneously reducing the likelihood of detecting false positives. Herein, we report a study using tile-based F-ratio analysis whereby four non-native analytes were spiked into diesel fuel at several concentrations ranging from 0 to 100 ppm. Spike level comparisons were performed in two regimes: comparing the spiked samples to the nonspiked fuel matrix and to each other at relative concentration factors of two. Redundant hits were algorithmically removed by refocusing the tiled results onto the original high resolution pixel level data. To objectively limit the tile-based F-ratio results to only features which are statistically likely to be true positives, we developed a combinatorial technique using null class comparisons, called null distribution analysis, by which we determined a statistically defensible F-ratio cutoff for the analysis of the hit list. After applying null distribution analysis, spiked analytes were reliably discovered at ∼1 to ∼10 ppm (∼5 to ∼50 pg using a 200:1 split), depending upon the degree of mass spectral selectivity and 2D chromatographic resolution, with minimal occurrence of false positives. To place the relevance of this work among other methods in this field, results are compared to those for pixel and peak table-based approaches.

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Development of a comprehensive, three-dimensional gas chromatograph (GC3) instrument is described. The instrument utilizes two six-port diaphragm valves as the interfaces between three, in-series capillary columns housed in a standard Agilent 6890 gas chromatograph fitted with a high data acquisition rate flame ionization detector. The modulation periods for sampling column one by column two and column two by column three are set so that a minimum of three slices (more commonly four or five) are acquired by the subsequent dimension resulting in both comprehensive and quantitative data. A 26-component test mixture and quantitative standards are analyzed using the GC3 instrument. A useful methodology for three-dimensional (3D) data analysis is evaluated, based on the chemometric technique parallel factor analysis (PARAFAC). Since the GC3 instrument produces trilinear data, we are able to use this powerful chemometric technique, which is better known for the analysis of two-dimensional (2D) separations with multichannel detection (e.g., GC x GC-TOFMS) or multiple samples (or replicates) of 2D data. Using PARAFAC, we mathematically separate (deconvolute) the 3D data "volume" for overlapped analytes (i.e., ellipsoids), provided there is sufficient chromatographic resolution in each of the three separation dimensions. Additionally, PARAFAC is applied to quantify analyte standards. For the quantitative analysis, it is demonstrated that PARAFAC may provide a 10-fold improvement in the signal-to-noise ratio relative to a traditional integration method applied to the raw, baseline-corrected data. The GC3 instrument obtains a 3D peak capacity of 3500 at a chromatographic resolution of one in each separation dimension. Furthermore, PARAFAC deconvolution provides a considerable enhancement in the effective 3D peak capacity.