Enhanced Chemical Analysis Using Parallel Column Gas Chromatography with Single-Detector Time-of-Flight Mass Spectrometry and Chemometric Analysis

Abstract

A parallel gas chromatographic instrument with time-offlight mass spectrometric detection (GC/TOF-MS) is reported. An injected sample is first split between two GC columns that provide complementary separations. The effluent from the two columns is recombined prior to detection with a single TOF-MS. Switching from single to parallel columns increases the chemical selectivity of a GC/TOF-MS data set without increasing analysis time, by doubling the number of peaks, or features, in the chromatographic dimension. The resulting analyzer can be used to reduce analysis times for partially resolved peaks. Simulations compare the quantitative precision of paralleland single-column instruments using the generalized rank annihilation method (GRAM). Results indicate that a parallel column GC/TOF-MS should substantially improve the chemical selectivity and quantitative precision of the analysis relative to a single-column instrument. For a column at half its peak capacity, for example, a singlecolumn instrument met the target precision less than 75% of the time, while a parallel-column instrument achieved 95% success. Parallel-column analyses of methyl tertbutyl ether (MTBE) and benzene in gasoline samples were also performed to support the simulation studies. An objective chromatographic standardization technique corrected for retention time shifts before GRAM was applied. Although MTBE and benzene were poorly resolved in the 40-s runs, chemometric techniques successfully quantitated them.

Qualitative and quantitative approaches in comprehensive two-dimensional gas chromatography

“…As seen in Section 3.5, chemometric techniques, such as principle component analysis (PCA) and component discriminate analysis (PCDA), have been used to find similarities and differences between samples [54][55][56][57][58]. Chemometrics techniques that simultaneously deconvolute and quantitate have been reported in GC × GC such as the generalized rank annihilation method (GRAM) and parallel factor analysis (PARAFAC) [48,[59][60][61][62]. Chemometric calibration techniques have also been applied to GC × GC, such as principal component regression (PCR), partial least squares (PLS), and multilinear partial least squares (NPLS) [48,[63][64][65].…”

“…There have been many reports using the GRAM method for both deconvolution and quantitation [59][60][61][62]. By comparing the multidimensional datasets from a sample and a standard, the concentrations and pure chromatographic and spectra profiles of the analytes can be determined [59].…”

“…By comparing the multidimensional datasets from a sample and a standard, the concentrations and pure chromatographic and spectra profiles of the analytes can be determined [59]. Since the method can deconvolute coeluting components, completely resolved peaks are not necessary for quantitation [60].…”

Trends in data processing of comprehensive two-dimensional chromatography: State of the art

“…This is an iterative and powerful method that has already been proven useful in deconvolution and quantification in 2D-chromatography [7,17,19,42,[44][45][46][47][48][49][50][51][52][53][54][55]. The PARAFAC model applied to a three-way data array can be described as follows:…”

Trilinear chemometric analysis of two-dimensional comprehensive gas chromatography–time-of-flight mass spectrometry data

“…With analytical instruments like GC×GC with flame ionization detection, calibration methods such as GRAM are able to deconvolute unknowns using two data sets (standard and sample) where the analytes of interest vary in concentration between the two data sets [12,[17][18][19][20][21][22]. Using trilinear data, such as GC × GC/TOFMS data, it is possible to deconvolute individual components from a group of partially overlapped components using a data set from only one sample.…”