Simultaneous deconvolution and re-construction of primary and secondary overlapping peak clusters in comprehensive two-dimensional gas chromatography.

In this study, simultaneous deconvolution and reconstruction of peak profiles in the first ((1)D) and second dimension ((2)D) of comprehensive two-dimensional (2D) gas chromatography (GC×GC) is achieved on the basis of the property of this new type of instrumental data. First, selective information, where only one component contributes to the peak elution window of a given modulation event, is employed for stepwise stripping of each (2)D peak with the help of pure components corresponding to that compound from the neighbouring modulations. Simulation based on an exponentially modified Gaussian (EMG) model aids this process, where the EMG represents the envelope of all (2)D peaks for that compound. The peak parameters can be restricted by knowledge of the pure modulated (2)D GC peaks derived from the same primary compound, since it is modulated into several fractions during the trapping and re-focusing process of the cryogenic modulation system according to the modulation period. Next, relative areas of all pure (2)D components of that compound are considered for reconstruction of the primary peak. This strategy of exploitation of the additional information provided by the second dimension of separation allows effective deconvolution of GC×GC datasets. Non-linear least squares curve fitting (NLLSCF) allows the resolved 2D chromatograms to be recovered. Accurate acquisition of the pure profiles in both (1)D and (2)D aids quantification of compositions and prediction of 2D retention parameters, which are of interest for qualitative and quantitative analysis. The ratio between the sum of squares of deconvolution residual and original peak response (R(rr)) is employed as an effective index to evaluate the resolution results. In this work, simulated and experimental examples are used to develop and test the proposed approach. Satisfactory performance for these studies is validated by minimum and maximum R(rr) values of 1.34e-7% and 1.09e-2%; and 1.0e-3% and 3.0e-1% for deconvolution of (1)D and (2)D peaks, respectively. Results suggest that the present technique is suitable for GC×GC data processing.