Gas chromatographic sensing on an optical fiber by mode-filtered light detection

A chemical sensor for gas phase measurements is reported which combines the principles of chemical separation and fiber optic detection. The analyzer incorporates an annular column Chromatographic sensor, constructed by inserting a polymer-clad optical fiber into a silica capillary. Light from a helium-neon laser is launched down the fiber, producing a steady intensity distribution within the fiber, but a low background of scattered light. When sample vapor is introduced to the sensor, and an analyte-rich volume interacts with the polymer cladding, Chromatographic retention is observed simultaneously with a change in the local refractive index of the cladding. An increase in cladding refractive index (RI) causes light to be coupled out of the fiber, with detection at a right-angle to the annular column length to provide optimum S/N ratio. This detection mechanism is called mode-filtered light detection. We report a gas Chromatographic separation on a 3.1 m annular column (320 microm i.d. silica tube, 228 microm o.d. fiber with a 12 microm fluorinated silicone clad) of methane, benzene, butanone and chlorobenzene in 6 min. The annular column length was reduced to 22 cm to function as a sensor, with selected organic vapors exhibiting unique retention times and detection selectivity. The detection selectivity is determined by the analyte RI and the partition coefficient into the cladding. The calculated limit of detection (LOD) for benzene vapor is 0.03% by volume in nitrogen, and several chlorinated species had LOD values less than 1%. For binary mixtures of organic vapors, the detected response appears to be the linear combination of the two organic standards, suggesting that the annular column may be useful as a general approach for designing chemical sensors that incorporate separation and optical detection principles simultaneously.     

Dynamic surface tension analysis of dodecyl sulfate association complexes

First, a novel calibration method is used to expand the current understanding of spherical drop growth and elongation that occurs during on-line measurements of surface pressure using the dynamic surface tension detector (DSTD). Using a novel surface tension calibration method, the drop radius is calculated as a function of time from experimental drop pressure data and compared to the theoretical drop radius calculated from volumetric flow rate. From this comparison, the drop volume at which the drop shape starts to deviate ( approximately 4 mul) from a spherical shape is readily observed and deviates more significantly by approximately 6 mul drop volume (5% deviation in the ideal spherical drop radius) for the capillary sensing tip employed in the DSTD. From this assessment of drop shape, an experimental method for precise drop detachment referred to as pneumatic drop detachment is employed at a drop volume of 2 mul (two second drops at 60 mul/min) in order to provide rapid dynamic surface tension measurements via the novel on-line calibration methodology. Second, the DSTD is used to observe and study kinetic information for surface-active molecules and association complexes adsorbing to an air-liquid drop interface. Dynamic surface tension measurements are made for sodium dodecyl sulfate (SDS) in the absence and presence of either tetra butyl ammonium (TBA) or chromium (III). Sensitive, indirect detection of chromium and other multiply charged metals at low concentrations is also investigated. The DSTD is utilized in examining the dynamic nature of SDS: cation association at the air-liquid interface of a growing drop. Either TBA or Cr(III) were found to substantially enhance the surface tension lowering of dodecyl sulfate (DS), but the surface tension lowering is accompanied by a considerable kinetic dependence. Essentially, the surface tension lowering of these DS: cation complexes is found to be a fairly slow process in the context of the two second DSTD measurement. The limit of detection for both SDS and chromium (III) is in the 300-400 part-per-billion (by mass) range.     

Multivariate selectivity as a metric for evaluating comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry subjected to chemometric peak deconvolution

Two-dimensional gas chromatography (GC x GC) coupled to time-of-flight mass spectrometry (TOFMS) [GC x GC-TOFMS)] is a highly selective technique well suited to analyzing complex mixtures. The data generated is information-rich, making it applicable to multivariate quantitative analysis and pattern recognition. One separation on a GC x GC-TOFMS provides retention times on two chromatographic columns and a complete mass spectrum for each component within the mixture. In this report, we demonstrate how GC x GC-TOFMS combined with trilinear chemometric techniques, specifically parallel factor analysis (PARAFAC) initiated by trilinear decomposition (TLD), results in a powerful analytical methodology for multivariate deconvolution. Using PARAFAC, partially resolved components in complex mixtures can be deconvoluted and identified without requiring a standard data set, signal shape assumptions or any fully selective mass signals. A set of four isomers (iso-butyl, sec-butyl, tert-butyl, and n-butyl benzenes) is used to investigate the practical limitations of PARAFAC for the deconvolution of isomers at varying degrees of chromatographic resolution and mass spectral selectivity. In this report, multivariate selectivity was tested as a metric for evaluating GC x GC-TOFMS data that is subjected to PARAFAC peak deconvolution. It was found that deconvolution results were best with multivariate selectivities over 0.18. Furthermore, the application of GC x GC-TOFMS followed by TLD/PARAFAC is demonstrated for a plant metabolite sample. A region of GC x GC-TOFMS data from a complex natural sample of a derivatized metabolic plant extract from Huilmo (Sisyrinchium striatum) was analyzed using TLD/PARAFAC, demonstrating the utility of this analytical technique on a natural sample containing overlapped analytes without selective ions or peak shape assumptions.     

Quantification of naphthalenes in jet fuel with GC x GC/Tri-PLS and windowed rank minimization retention time alignment

Comprehensive, two-dimensional gas chromatography (GC x GC) is used in conjunction with trilinear partial least squares (Tri-PLS) to quantify the percent weight of naphthalenes (two-ring aromatic compounds) in jet fuel samples. The increased peak capacity and selectivity of GC x GC makes the technique attractive for the rapid, and possibly less tedious analysis of jet fuel. The analysis of complex mixtures by GC x GC is further enhanced through the use of chemometric techniques, including those designed for use on 2-D data such as Tri-PLS. Unfortunately, retention time variation, unless corrected, can be an impediment to chemometric analysis. Previous work has demonstrated that the effects of retention time variation can be mitigated in sub-regions of GC x GC chromatograms through the application of an objective retention time alignment algorithm based on rank minimization. Building upon this previous work, it is demonstrated here that the effects of retention time variation can be mitigated throughout an entire GC x GC chromatogram with an objective retention time alignment algorithm based on windowed rank minimization alignment. A significant decrease in calibration error is observed when the algorithm is applied to chromatograms prior to construction of Tri-PLS models. Fourteen jet fuel samples with known weight percentages of naphthalenes (ASTM D1840) were obtained. Each sample was subjected to five replicate five-minute GC x GC separations over a period of two days. A subset of nine samples spanning the range of weight percentages of naphthalenes was chosen as a calibration set and Tri-PLS calibration models were subsequently developed in order to predict the naphthalene content of the samples from the GC x GC chromatograms of the remaining five samples. Calibration models constructed from GC x GC chromatograms that were retention time corrected are shown to exhibit a root mean square error of prediction of roughly half that of calibration models constructed from uncorrected chromatograms. The error of prediction is lowered further to a value that nearly matches the uncertainty in the standard percent weight values (ca. 1% of the median percent volume value) when the aligned chromatograms are truncated to include only regions of the chromatogram populated by naphthalenes and compounds of similar polarity and boiling point.     

Unsupervised parameter optimization for automated retention time alignment of severely shifted gas chromatographic data using the piecewise alignment algorithm

Simulated chromatographic separations were used to study the performance of piecewise retention time alignment and to demonstrate automated unsupervised (without a training set) parameter optimization. The average correlation coefficient between the target chromatogram and all remaining chromatograms in the data set was used to optimize the alignment parameters. This approach frees the user from providing class information and makes the alignment algorithm applicable to classifying completely unknown data sets. The average peak in the raw simulated data set was shifted up to two peak-widths-at-base (average relative shift=2.0) and after alignment the average relative shift was improved to 0.3. Piecewise alignment was applied to severely shifted GC separations of gasolines and reformate distillation fraction samples. The average relative shifts in the raw gasolines and reformates data were 4.7 and 1.5, respectively, but after alignment improved to 0.5 and 0.4, respectively. The effect of piecewise alignment on peak heights and peak areas is also reported. The average relative difference in peak height was -0.20%. The average absolute relative difference in area was 0.15%.     

Analysis of bacteria by pyrolysis gas chromatography-differential mobility spectrometry and isolation of chemical components with a dependence on growth temperature

Pyrolysis gas chromatography-differential mobility spectrometry (py-GC-DMS) analysis of E. coli, P. aeruginosa, S. warneri and M. luteus, grown at temperatures of 23, 30, and 37 degrees C, provided data sets of ion intensity, retention time, and compensation voltage for principal component analysis. Misaligned chromatographic axes were treated using piecewise alignment, the impact on the degree of class separation (DCS) of clusters was minor. The DCS, however, was improved between 21 to 527% by analysis of variance with Fisher ratios to remove chemical components independent of growth temperature. The temperature dependent components comprised 84% of all peaks in the py-GC-DMS analysis of E. coli and were attributed to the pyrolytic decomposition of proteins rather than lipids, as anticipated. Components were also isolated in other bacteria at differing amounts: 41% for M. luteus, 14% for P. aeruginosa, and 4% for S. warneri, and differing patterns suggested characteristic dependence on temperature of growth for these bacteria. These components are anticipated to have masses from 100 to 200 Da by inference from differential mobility spectra.     

Identification and evaluation of cycling yeast metabolites in two-dimensional comprehensive gas chromatography-time-of-flight-mass spectrometry data

A yeast metabolome exhibiting oscillatory behavior was analyzed using comprehensive two-dimensional gas chromatography-time-of-flight-mass spectrometry (GC x GC-TOF-MS) and in-house developed data analysis software methodology, referred to as a signal ratio method (S(ratio) method). In this study, 44 identified unique metabolites were found to exhibit cycling, with a depth-of-modulation amplitude greater than three. After the initial locations are found using the S(ratio) software, and identified preliminarily using ChromaTOF software, the refined mass spectra and peak volumes were subsequently obtained using parallel factor analysis (PARAFAC). The peak volumes provided by PARAFAC deconvolution provide a measurement of the cycling depth-of-modulation amplitude that is more accurate than the initial S(ratio) information (which serves as a rapid screening procedure to find the cycling metabolites while excluding peaks that do not cycle). The S(ratio) reported is a rapid method to determine the depth-of-modulation while not constraining the search to specific cycling frequencies. The phase delay of the cycling metabolites ranged widely in relation to the oxygen consumption cycling pattern.     

High-speed gas chromatography: the importance of instrumentation optimization and the elimination of extra-column band broadening

This review provides a summary of chromatographic theory as it applies to high-speed gas chromatography. A novel method for determining the optimal linear flow velocity, u (opt), from specific experimental parameters, is discussed. An in-depth theoretical understanding of u (opt) and its relation to experimental parameters is presented, in the absence of extra-column band broadening, as a means of method evaluation and optimization. Recent developments in high-speed GC are discussed, in the context of the theory presented within this review, to ascertain the influence of extra-column band broadening. The theory presented herein can be used as a means of evaluating the various areas of GC instrumentation (injection, separation, detection, etc.) that need further development to further minimize the effects of extra-column band broadening. The theoretical framework provided in this review, can be, and is, readily used to evaluate high-speed GC results presented in the literature, and thus, the general practitioner may more readily select a specific capillary length and/or internal diameter for a given application. For example, it is theoretically shown, and prior work cited, that demonstrates a peak width of approximately 1 ms is readily achievable in GC, when extra-column band broadening is eliminated.     

Trilinearity deviation ratio: A new metric for chemometric analysis of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry data

Comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC–TOFMS) is a well-established instrumental platform for complex samples. However, chemometric data analysis is often required to fully extract useful information from the data. We demonstrate that retention time shifting from one modulation to the next, Δ²t_R, is not sufficient alone to quantitatively describe the trilinearity of a single GC × GC–TOFMS run for the purpose of predicting the performance of the chemometric method parallel factor analysis (PARAFAC). We hypothesize that analyte peak width on second dimension separations, ²W_b, also impacts trilinearity, along with Δ²t_R. The term trilinearity deviation ratio, TDR, which is Δ²t_R normalized by ²W_b, is introduced as a quantitative metric to assess accuracy for PARAFAC of a GC × GC–TOFMS data cube. We explore how modulation ratio, M_R, modulation period, P_M, temperature programming rate, T_ramp, sampling phase (in-phase and out-of-phase), and signal-to-noise ratio, S/N, all play a role in PARAFAC performance in the context of TDR. Use of a P_M in the 1–2 s range provides an optimized peak capacity for the first dimension separation (500–600) for a 30 min run, with an adequate peak capacity for the second dimension separation (12–15), concurrent with an optimized two-dimensional peak capacity (6000–7500), combined with sufficiently low TDR values (0–0.05) to facilitate low quantitative errors with PARAFAC (0–0.5%). In contrast, use of a P_M in the 5 s or greater range provides a higher peak capacity on the second dimension (30–35), concurrent with a lower peak capacity on the first dimension (100–150) for a 30 min run, and a slightly reduced two-dimensional peak capacity (3000–4500), and furthermore, the data are not sufficiently trilinear for the more retained second dimension peaks in order to directly use PARAFAC with confidence.     

Development and application of a comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry method for the analysis of l-β-methylamino-alanine in human tissue

l-β-Methylamino-alanine (BMAA) has been proposed as a worldwide contributor to neurodegenerative diseases, including Parkinson dementia complex (PDC) of Guam and Alzheimer's disease (AD). Recent conflicting reports of the presence of this amino acid in human brain from patients affected by these diseases have made it necessary to develop methods that provide unambiguous detection in complex samples. Comprehensive two-dimensional gas chromatography coupled with time-of-flight-mass-spectrometry analysis (GC × GC–TOFMS) followed by a targeted Parallel Factor Analysis (PARAFAC) deconvolution method has been used recently in metabolomic investigations to separate, identify, and quantify components of complex biological specimens. We have extended and applied this methodology to the toxicological problem of detecting BMAA in extracts of brain tissue. Our results show that BMAA can be isolated from closely eluting compounds and detected in trace amounts in extracts of brain tissue spiked with low levels of this analyte, ranging from 2.5 ppb to 50 ppb, with a limit of detection (LOD) of 0.7 ppb. This new method was sufficiently sensitive to detect BMAA in cerebral extracts of mice fed BMAA. This optimized approach was then applied to analyze tissue from humans; however, no BMAA was detected in the brain extracts from controls or patients with PDC or AD. Our results demonstrate the application of multidimensional chromatography–mass spectrometry methods and computational deconvolution analysis to the problem of detecting trace amounts of a potential toxin in brain extracts from mice and humans.