Co-reporter:Nathanial E. Watson, Sarah E. Prebihalo, Robert E. Synovec
Analytica Chimica Acta 2017 Volume 983(Volume 983) pp:
Publication Date(Web):29 August 2017
DOI:10.1016/j.aca.2017.06.017
•A four-way PARAFAC method is presented to analyze GC3-TOFMS data.•The method overcomes challenges of reducing rank prior to PARAFAC analysis.•All 42 target analyte spectra were successfully resolved and identified.Comprehensive three-dimensional gas chromatography with time-of-flight mass spectrometry (GC3-TOFMS) creates an opportunity to explore a new paradigm in chemometric analysis. Using this newly described instrument and the well understood Parallel Factor Analysis (PARAFAC) model we present one option for utilization of the novel GC3-TOFMS data structure. We present a method which builds upon previous work in both GC3 and targeted analysis using PARAFAC to simplify some of the implementation challenges previously discovered. Conceptualizing the GC3-TOFMS instead as a one-dimensional gas chromatograph with GC × GC-TOFMS detection we allow the instrument to create the PARAFAC target window natively. Each first dimension modulation thus creates a full GC × GC-TOFMS chromatogram fully amenable to PARAFAC. A simple mixture of 115 compounds and a diesel sample are interrogated through this methodology. All test analyte targets are successfully identified in both mixtures. In addition, mass spectral matching of the PARAFAC loadings to library spectra yielded results greater than 900 in 40 of 42 test analyte cases. Twenty-nine of these cases produced match values greater than 950.Download high-res image (172KB)Download full-size image
Co-reporter:Nathanial E. Watson, H. Daniel Bahaghighat, Ke Cui, and Robert E. Synovec
Analytical Chemistry 2017 Volume 89(Issue 3) pp:
Publication Date(Web):December 30, 2016
DOI:10.1021/acs.analchem.6b04112
Development of comprehensive, three-dimensional (3D) gas chromatography with time-of-flight mass spectrometric detection (GC3/TOFMS) is described. This instrument provides four dimensions (4D) of chemical selectivity and includes significant improvements to total selectivity (mass spectrometric and chromatographic), peak identification, and operational temperature range relative to previous models of the GC3 reported. The new instrumental design and data output are evaluated and illustrated via two samples, a 115-component test mixture and a diesel fuel spiked with several compounds, for the purpose of illustrating the chemical selectivity benefits of this instrumental platform. Useful approaches to visualize the 4D data are presented. The GC3/TOFMS instrument experimentally achieved total peak capacity, nc,3D, ranging from 5000 to 9600 (x̅ = 7000, s = 1700) for 10 representative analytes for 50 min separations with component dimensional peak capacities averaging 406, 3.6, and 4.9 for 1D, 2D, and 3D, respectively. Particularly, GC3/TOFMS achieved a combined 2D × 3D peak capacity ranging from 10 to 26 (x̅ = 17.6, s = 5.0), which is similar to what is achieved by 2D alone in a GC × GC operating at equivalent modulation period conditions. The analytical benefits of employing three varied chemical selectivities in the 3D separation coupled with TOFMS are illustrated through the separation and detection of 1,6-dichlorohexane and cyclohexyl isothiocyanate as part of the diesel fuel analysis.
Co-reporter:Brian D. Fitz, Robert E. Synovec
Analytica Chimica Acta 2016 Volume 913() pp:160-170
Publication Date(Web):24 March 2016
DOI:10.1016/j.aca.2016.01.045
•Low thermal mass gas chromatography, LTM-GC, was coupled to TOFMS.•Novel approach for the analysis of fast LTM-GC-TOFMS data is presented.•A traditional peak capacity of 340 was achieved in a 2 min temperature programmed separation.•The mass cluster method achieved an effective peak capacity of 10,000 in 2 min.•The mass cluster method is useful in conjunction with current chemometric tools.Implementation of a data reduction and visualization method for use with high-speed gas chromatography and time-of-flight mass spectrometry (GC-TOFMS) is reported. The method, called the “2D m/z cluster method” facilitates analyte detection, deconvolution, and identification, by accurately measuring peak widths and retention times using a fast TOFMS sampling frequency (500 Hz). Characteristics and requirements for high speed GC are taken into consideration: fast separations with narrow peak widths and high peak capacity, rapid data collection rate, and effective peak deconvolution. Transitioning from standard GC (10–60+ minute separations) to fast GC (1–10 min separations) required consideration of how to properly analyze the data. This report validates use of the 2D m/z cluster method with newly developed GC technology that produces ultra-fast separations (∼1 min) with narrow analyte peak widths. Low thermal mass gas chromatography (LTM-GC) operated at a heating rate of 250 °C/min coupled to a LECO Pegasus III TOFMS analyzed a 115 component test mixture in 120 s with peak widths-at-base, wb (4σ), of 350 ms (average) to produce a separation with a high peak capacity, nc ∼ 340 (at unit resolution Rs = 1). The 2D m/z cluster method is shown to separate overlapped analytes to a limiting Rs ∼ 0.03, so the effective peak capacity was increased nearly 30-fold to nc ∼10,000 in the 120 s separation. The method, when coupled with LTM-GC-TOFMS, is demonstrated to provide unambiguous peak rank (i.e. the number of analytes per overlapped peak in the total ion current (TIC)), by visualizing locations of pure and chromatographically overlapped m/z. Hence, peak deconvolution and identification using MCR-ALS (multivariate curve resolution – alternating least squares) is demonstrated.
Co-reporter:Nathanial E. Watson, Brendon A. Parsons, Robert E. Synovec
Journal of Chromatography A 2016 Volume 1459() pp:101-111
Publication Date(Web):12 August 2016
DOI:10.1016/j.chroma.2016.06.067
•Discovery based analysis was applied to a benchmark yeast metabolome dataset.•Tile-based Fisher Ratio analysis was validated against a previously analyzed dataset.•Null distribution analysis was utilized for threshold determination to optimize data mining.•94 up-/down-regulated metabolites were identified above the threshold.•The analysis was replicated four times and all replicates were in excellent agreement with the benchmark dataset.Performance of tile-based Fisher Ratio (F-ratio) data analysis, recently developed for discovery-based studies using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC–TOFMS), is evaluated with a metabolomics dataset that had been previously analyzed in great detail, but while taking a brute force approach. The previously analyzed data (referred to herein as the benchmark dataset) were intracellular extracts from Saccharomyces cerevisiae (yeast), either metabolizing glucose (repressed) or ethanol (derepressed), which define the two classes in the discovery-based analysis to find metabolites that are statistically different in concentration between the two classes. Beneficially, this previously analyzed dataset provides a concrete means to validate the tile-based F-ratio software. Herein, we demonstrate and validate the significant benefits of applying tile-based F-ratio analysis. The yeast metabolomics data are analyzed more rapidly in about one week versus one year for the prior studies with this dataset. Furthermore, a null distribution analysis is implemented to statistically determine an adequate F-ratio threshold, whereby the variables with F-ratio values below the threshold can be ignored as not class distinguishing, which provides the analyst with confidence when analyzing the hit table. Forty-six of the fifty-four benchmarked changing metabolites were discovered by the new methodology while consistently excluding all but one of the benchmarked nineteen false positive metabolites previously identified.
Co-reporter:Brooke C. Reaser, Song Yang, Brian D. Fitz, Brendon A. Parsons, Mary E. Lidstrom, Robert E. Synovec
Journal of Chromatography A 2016 Volume 1432() pp:111-121
Publication Date(Web):5 February 2016
DOI:10.1016/j.chroma.2015.12.088
•Novel analytical workflow to determine time-dependent 13C-labeling.•Non-targeted analyte indexing and deconvolution at ultra-low resolution.•Principal component analysis to identify and accurately quantify 13C-labeling.•Elucidation of 13C-labeling time course profiles using principal component analysis.A novel analytical workflow is presented for the analysis of time-dependent 13C-labeling of the metabolites in the methylotrophic bacterium Methylobacterium extorquens AM1 using gas chromatography time-of-flight mass spectrometry (GC-TOFMS). Using 13C-methanol as the substrate in a time course experiment, the method provides an accurate determination of the number of carbons converted to the stable isotope. The method also extracts a quantitative isotopic dilution time course profile for 13C uptake of each metabolite labeled that could in principle be used to obtain metabolic flux rates. The analytical challenges encountered require novel analytical platforms and chemometric techniques. GC-TOFMS offers advanced separation of mixtures, identification of individual components, and high data density for the application of advanced chemometrics. This workflow combines both novel and traditional chemometric techniques, including the recently reported two-dimensional mass cluster plot method (2D m/z cluster plot method) as well as principal component analysis (PCA). The 2D m/z cluster plot method effectively indexed all metabolites present in the sample and deconvoluted metabolites at ultra-low chromatographic resolution (RS ≈ 0.04). Using the pure mass spectra extracted, two PCA models were created. Firstly, PCA was used on the first and last time points of the time course experiment to determine and quantify the extent of 13C uptake. Secondly, PCA modeled the full time course in order to quantitatively extract the time course profile for each metabolite. The 2D m/z cluster plot method found 152 analytes (metabolites and reagent peaks), with 54 pure analytes, and 98 were convoluted, with 65 of the 98 requiring mathematical deconvolution. Of the 152 analytes surveyed, 83 were metabolites determined by the PCA model to have incorporated 13C while 69 were determined to be either metabolites or reagent peaks that remained unlabeled.
Co-reporter:Chris E. Freye, Robert E. Synovec
Talanta 2016 Volume 161() pp:675-680
Publication Date(Web):1 December 2016
DOI:10.1016/j.talanta.2016.09.002
•A high temperature diaphragm valve is used as a modulator with time-of-flight mass spectrometry detection.•A flow rate of 3 ml/min on the second dimension separation was applied.•Diesel fuel is studied to demonstrate instrument practicality.A high temperature diaphragm valve-based two-dimensional (2D) gas chromatography (GC×GC) with time-of-flight mass spectrometry (TOFMS) instrument, with the valve mounted directly in the GC oven, is demonstrated with separations up to 325 °C. Use of the diaphragm valve allowed for the use of uncoupled carrier gas flows for 1D (first column dimension) and 2D (second column dimension), with a 1D flow rate of 1 ml/min, and a 2D flow rate 3 ml/min. The 3 ml/min flow rate on 2D was selected to ensure compatibility with most TOFMS detectors. For valve-based modulation, a 5 µl sample loop coupled with a 60 ms pulse width was selected, providing sufficient sensitivity concurrent with an acceptable 2D peak capacity. A 44-component mixture of alkanes, alcohols, and polyaromatic hydrocarbons (including n-alkanes of heptane to triacontane) whose boiling points range from 98 °C to 450 °C was used to initially study instrument performance. For a 120 min separation and a modulation period PM of 2 s, average peak widths-at-base of 10 s and 94 ms were achieved for the alkanes on the 1D and 2D dimensions, respectively. Hence, the 1D peak capacity is 1nc~700, and the 2D peak capacity can in principle be 2nc~20. Thus the ideal 2D peak capacity could in principle approach nc,2D~14,000 using the 120 min 1D run time. The limit of detection (LOD) for docosane, a representative analyte, was determined to be 1.5 ppm injected concentration when 2 µl of liquid sample was injected with a 20:1 split. A separation of diesel fuel demonstrated the practical utility of the instrument with this complex sample using a relatively fast run time of 20 min and a short modulation period PM of 1 s. Average peak widths-at-base of 5.4 s and 166 ms were achieved on the 1D and 2D dimensions, respectively. This yielded a 1nc~220 and a 2nc~ 6. Therefore, the 2D peak capacity is nc,2D~1320 with the 20 min diesel separation.
Co-reporter:Chris E. Freye, Brian D. Fitz, Matthew C. Billingsley, Robert E. Synovec
Talanta 2016 Volume 153() pp:203-210
Publication Date(Web):1 June 2016
DOI:10.1016/j.talanta.2016.03.016
•Kerosene-based rocket fuels are analyzed via GC×GC–FID.•Modulation is achieved using a high temperature diaphragm valve mounted in the oven.•Chemometric methods are used to regress GC×GC–FID data against ASTM values.•Specific compound classes and physical properties are chemometrically modeled.The chemical composition and several physical properties of RP-1 fuels were studied using comprehensive two-dimensional (2D) gas chromatography (GC×GC) coupled with flame ionization detection (FID). A “reversed column” GC×GC configuration was implemented with a RTX-wax column on the first dimension (1D), and a RTX-1 as the second dimension (2D). Modulation was achieved using a high temperature diaphragm valve mounted directly in the oven. Using leave-one-out cross-validation (LOOCV), the summed GC×GC–FID signal of three compound-class selective 2D regions (alkanes, cycloalkanes, and aromatics) was regressed against previously measured ASTM derived values for these compound classes, yielding root mean square errors of cross validation (RMSECV) of 0.855, 0.734, and 0.530 mass%, respectively. For comparison, using partial least squares (PLS) analysis with LOOCV, the GC×GC–FID signal of the entire 2D separations was regressed against the same ASTM values, yielding a linear trend for the three compound classes (alkanes, cycloalkanes, and aromatics), yielding RMSECV values of 1.52, 2.76, and 0.945 mass%, respectively. Additionally, a more detailed PLS analysis was undertaken of the compounds classes (n-alkanes, iso-alkanes, mono-, di-, and tri-cycloalkanes, and aromatics), and of physical properties previously determined by ASTM methods (such as net heat of combustion, hydrogen content, density, kinematic viscosity, sustained boiling temperature and vapor rise temperature). Results from these PLS studies using the relatively simple to use and inexpensive GC×GC–FID instrumental platform are compared to previously reported results using the GC×GC–TOFMS instrumental platform.
Co-reporter:Brendon A. Parsons, Luke C. Marney, W. Christopher Siegler, Jamin C. Hoggard, Bob W. Wright, and Robert E. Synovec
Analytical Chemistry 2015 Volume 87(Issue 7) pp:3812
Publication Date(Web):March 18, 2015
DOI:10.1021/ac504472s
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.
Co-reporter:David K. Pinkerton, Brendon A. Parsons, Todd J. Anderson, Robert E. Synovec
Analytica Chimica Acta 2015 Volume 871() pp:66-76
Publication Date(Web):29 April 2015
DOI:10.1016/j.aca.2015.02.040
•The percent error for PARAFAC with temperature programmed GC × GC–TOFMS is studied.•The percent error depends on the trilinearity deviation ratio (TDR) and modulation ratio (MR).•TDR is the second dimension retention time shift normalized by second dimension peak width.•Low modulation periods of 1–2 s produce trilinear data with low percent error from PARAFAC quantification.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, Δ2tR, 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, 2Wb, also impacts trilinearity, along with Δ2tR. The term trilinearity deviation ratio, TDR, which is Δ2tR normalized by 2Wb, is introduced as a quantitative metric to assess accuracy for PARAFAC of a GC × GC–TOFMS data cube. We explore how modulation ratio, MR, modulation period, PM, temperature programming rate, Tramp, 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 PM 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 PM 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.
Co-reporter:Brian D. Fitz, Brandyn C. Mannion, Khang To, Trinh Hoac, Robert E. Synovec
Journal of Chromatography A 2015 Volume 1392() pp:82-90
Publication Date(Web):1 May 2015
DOI:10.1016/j.chroma.2015.03.009
•Injection methods for low thermal mass gas chromatography (LTM-GC) were evaluated.•Liquid, solid phase micro-extraction (SPME) and direct vapor samples were evaluated.•Cryo-focusing injection with LTM-GC provided a peak capacity of 270 in 60 s.•LTM-GC was able to focus analytes sufficiently without external cryogenic trapping.•LTM-GC–TOFMS was demonstrated with SPME sampling of banana peel vapor.Low thermal mass gas chromatography (LTM-GC) was evaluated for rapid, high peak capacity separations with three injection methods: liquid, headspace solid phase micro-extraction (HS-SPME), and direct vapor. An Agilent LTM equipped with a short microbore capillary column was operated at a column heating rate of 250 °C/min to produce a 60 s separation. Two sets of experiments were conducted in parallel to characterize the instrumental platform. First, the three injection methods were performed in conjunction with in-house built high-speed cryo-focusing injection (HSCFI) to cryogenically trap and re-inject the analytes onto the LTM-GC column in a narrower band. Next, the three injection methods were performed natively with LTM-GC. Using HSCFI, the peak capacity of a separation of 50 nl of a 73 component liquid test mixture was 270, which was 23% higher than without HSCFI. Similar peak capacity gains were obtained when using the HSCFI with HS-SPME (25%), and even greater with vapor injection (56%). For the 100 μl vapor sample injected without HSCFI, the preconcentration factor, defined as the ratio of the maximum concentration of the detected analyte peak relative to the analyte concentration injected with the syringe, was determined to be 11 for the earliest eluting peak (most volatile analyte). In contrast, the preconcentration factor for the earliest eluting peak using HSCFI was 103. Therefore, LTM-GC is demonstrated to natively provide in situ analyte trapping, although not to as great an extent as with HSCFI. We also report the use of LTM-GC applied with time-of-flight mass spectrometry (TOFMS) detection for rapid, high peak capacity separations from SPME sampled banana peel headspace.
Co-reporter:Brian D. Fitz, Brooke C. Reaser, David K. Pinkerton, Jamin C. Hoggard, Kristen J. Skogerboe, and Robert E. Synovec
Analytical Chemistry 2014 Volume 86(Issue 8) pp:3973
Publication Date(Web):March 24, 2014
DOI:10.1021/ac5004344
A novel data reduction and representation method for gas chromatography time-of-flight mass spectrometry (GC-TOFMS) is presented that significantly facilitates separation visualization and analyte peak deconvolution. The method utilizes the rapid mass spectral data collection rate (100 scans/s or greater) of current generation TOFMS detectors. Chromatographic peak maxima (serving as the retention time, tR) above a user specified signal threshold are located, and the chromatographic peak width, W, are determined on a per mass channel (m/z) basis for each analyte peak. The peak W (per m/z) is then plotted against its respective tR (with 10 ms precision) in a two-dimensional (2D) format, producing a cluster of points (i.e., one point per peak W versus tR in the 2D plot). Analysis of GC-TOFMS data by this method produces what is referred to as a two-dimensional mass channel cluster plot (2D m/z cluster plot). We observed that adjacent eluting (even coeluting) peaks in a temperature programmed separation can have their peak W vary as much as ∼10–15%. Hence, the peak W provides useful chemical selectivity when viewed in the 2D m/z cluster plot format. Pairs of overlapped analyte peaks with one-dimensional GC resolution as low as Rs ≈ 0.03 can be visually identified as fully resolved in a 2D m/z cluster plot and readily deconvoluted using chemometrics (i.e., demonstrated using classical least-squares analysis). Using the 2D m/z cluster plot method, the effective peak capacity of one-dimensional GC separations is magnified nearly 40-fold in one-dimensional GC, and potentially ∼100-fold in the context of comparing it to a two-dimensional separation. The method was studied using a 73 component test mixture separated on a 30 m × 250 μm i.d. RTX-5 column with a LECO Pegasus III TOFMS.
Co-reporter:Benjamin Kehimkar, Jamin C. Hoggard, Luke C. Marney, Matthew C. Billingsley, Carlos G. Fraga, Thomas J. Bruno, Robert E. Synovec
Journal of Chromatography A 2014 Volume 1327() pp:132-140
Publication Date(Web):31 January 2014
DOI:10.1016/j.chroma.2013.12.060
•A ‘reversed column’ GC × GC format was used to separate ten RP-1 fuels.•Partial least squares (PLS) analysis was used to analyze the GC × GC–TOFMS data.•Replicate data sets were separately analyzed using leave-one-out cross validation.•Connections between fuel composition and physical properties were investigated.•Compounds that appeared most influential for physical properties were identified.There is an increased need to more fully assess and control the composition of kerosene-based rocket propulsion fuels such as RP-1. In particular, it is critical to make better quantitative connections among the following three attributes: fuel performance (thermal stability, sooting propensity, engine specific impulse, etc.), fuel properties (such as flash point, density, kinematic viscosity, net heat of combustion, and hydrogen content), and the chemical composition of a given fuel, i.e., amounts of specific chemical compounds and compound classes present in a fuel as a result of feedstock blending and/or processing. Recent efforts in predicting fuel chemical and physical behavior through modeling put greater emphasis on attaining detailed and accurate fuel properties and fuel composition information. Often, one-dimensional gas chromatography (GC) combined with mass spectrometry (MS) is employed to provide chemical composition information. Building on approaches that used GC–MS, but to glean substantially more chemical information from these complex fuels, we recently studied the use of comprehensive two dimensional (2D) gas chromatography combined with time-of-flight mass spectrometry (GC × GC–TOFMS) using a “reversed column” format: RTX-wax column for the first dimension, and a RTX-1 column for the second dimension. In this report, by applying chemometric data analysis, specifically partial least-squares (PLS) regression analysis, we are able to readily model (and correlate) the chemical compositional information provided by use of GC × GC–TOFMS to RP-1 fuel property information such as density, kinematic viscosity, net heat of combustion, and so on. Furthermore, we readily identified compounds that contribute significantly to measured differences in fuel properties based on results from the PLS models. We anticipate this new chemical analysis strategy will have broad implications for the development of high fidelity composition-property models, leading to an improved approach to fuel formulation and specification for advanced engine cycles.
Co-reporter:Song Yang, Jamin C. Hoggard, Mary E. Lidstrom, Robert E. Synovec
Journal of Chromatography A 2013 Volume 1317() pp:175-185
Publication Date(Web):22 November 2013
DOI:10.1016/j.chroma.2013.08.059
•A comprehensive list of 13C labeled metabolites from M. extorquens AM1 were generated.•131 metabolites from M. extorquens AM1 were analyzed, with 40 significantly labeled.•A match value (MV) based approach was used to rank the extent of isotopic labeling.•Incorporation of 13C into M. extorquens AM1 should assist metabolic pathway elucidation.Herein, we report the identification of isotopically labeled metabolite peaks (or the lack of labeling) between sets of GC–MS data from Methylobacterium extorquens AM1. M. extorquens AM1 is one of the best-characterized model organisms for the study of C1 metabolism in methylotrophic bacteria, a diverse group of microbes that can use reduced one-carbon (C1) sources, such as methanol and methane as a sole source for both energy generation and carbon assimilation. Application of a match value (MV) based metric was used to rank the metabolite peaks in the data from those exhibiting the most mass spectral indications of labeling, to those not exhibiting any indications of labeling. The MV-based ranking corresponded well with analyst interpretation of the mass spectra. The MV-based method was initially demonstrated and validated using a mixture of 21 standards with data sets generated for mixtures at natural abundance, a mixture with 6 of the compounds labeled, and a 1:1 mixture of the natural abundance and labeled mixtures. Experimental data from TMS-derivatized extracts from the bacterium M. extorquens AM1 grown with natural abundance or 13C-labeled methanol as the carbon source were analyzed. Of 131 peaks considered for the analysis of M. extorquens AM1, the 40 peaks ranked highest for indications of 13C labeling were all found to be labeled, while those peaks ranked lower progressed from peaks for which labeling was uncertain, to a larger number of peaks that were clearly not labeled. The list of peaks determined to be labeled forms a library of compounds that are known to be labeled following the methanol metabolic pathway in M. extorquens AM1 that can be further investigated in future work, e.g. fluxomic studies.
Co-reporter:Luke C. Marney, Stephen C. Kolwicz Jr., Rong Tian, Robert E. Synovec
Talanta 2013 Volume 108() pp:123-130
Publication Date(Web):15 April 2013
DOI:10.1016/j.talanta.2013.03.005
Co-reporter:Ryan B. Wilson, Jamin C. Hoggard, Robert E. Synovec
Talanta 2013 Volume 103() pp:95-102
Publication Date(Web):15 January 2013
DOI:10.1016/j.talanta.2012.10.013
Co-reporter:Benjamin Kehimkar, Jamin C. Hoggard, Jeremy S. Nadeau, Robert E. Synovec
Talanta 2013 Volume 103() pp:267-275
Publication Date(Web):15 January 2013
DOI:10.1016/j.talanta.2012.10.043
An algorithm, referred to as targeted mass spectral ratio analysis (TMSRA) is presented whereby the ratios between intensities as a function of mass channel (m/z) of a target analyte mass spectrum are used to automatically determine which m/z are sufficiently pure to quantify the analyte in a sample gas chromatogram. The standard perfluorotributylamine (PFTBA) was used to evaluate the reproducibility of the collected mass spectra, which aided in selecting a mass spectral threshold for TMSRA application to a subsequent case study. Results with PFTBA suggested that a threshold of all m/z at or above 1% of the highest recorded m/z intensity should be included for targeted analysis. For the case study, 1-heptene was selected as the target analyte and n-heptane was selected as the interfering compound. These two compounds were chosen since their mass spectra are very similar. Chromatographic data containing a pure peak for these analytes were extracted, and mathematically added at various temporal offsets to generate various degrees of chromatographic resolution, Rs, for the purpose of evaluating algorithm performance, and indeed, TMSRA successfully quantified 1-heptene. At the higher Rs studied (0.6≤Rs≤1.5) a deviation within±1% and a RSD generally below 1% were achieved for 1-heptene quantification. As the Rs decreased, the deviation and RSD both increased. At a Rs=0, a deviation of ∼9% and a RSD of∼9% were achieved.Highlights► A novel method for choosing selective m/z for quantification in crowded GC–MS data. ► With overlapping peaks in a GC–MS chromatogram, selective m/z are needed for resolution. ► The algorithm automatically selects sufficiently pure m/z for target analytes. ► Algorithm dependence on chromatographic resolution has been studied. ► Analytes with overlap and mass spectral interference are successfully quantified.
Co-reporter:Ryan B. Wilson, Jamin C. Hoggard, and Robert E. Synovec
Analytical Chemistry 2012 Volume 84(Issue 9) pp:4167
Publication Date(Web):March 26, 2012
DOI:10.1021/ac300481k
Peak capacity production (i.e., peak capacity per separation run time) is substantially improved for gas chromatography–time-of-flight mass spectrometry (GC-TOFMS) and applied to the fast separation of complex samples. The increase in peak capacity production is achieved by selecting appropriate experimental conditions based on theoretical modeling of on-column band broadening, and by reducing the injection pulse width. Modeling to estimate the on-column band broadening from experimental parameters provided insight for the potential of achieving GC separations in the absence of off-column band broadening, i.e., the additional band broadening not due to the on-column separation process. To optimize GC-TOFMS separations collected with a commercial instrumental platform, off-column band broadening from injection and detection needed to be significantly reduced. Specifically for injection, a commercially available thermal modulator is adapted and applied (referred to herein as thermal injection) to provide a narrow injection pulse, while the TOFMS provided a data collection rate of 500 Hz, initially averaged to 100 Hz for data storage. The use of long, relatively narrow open tubular capillary columns and a 30 °C/min programming rate were explored for GC-TOFMS, specifically a 20 m, 100 μm inner diameter (i.d.) capillary column with a 0.4 μm film thickness to benefit column capacity, operated slightly below the optimal average linear gas velocity (at ∼2 mL/min, due to the flow rate constraint of the TOFMS). Standard autoinjection with a 1:100 split resulted in an average peak width of ∼1.2 s, hence a peak capacity production of 50 peaks/min. Metabolites in the headspace of urine were sampled by solid-phase microextraction (SPME), followed by thermal injection and a ∼7 min GC separation (with a ∼6 min separation time window), producing ∼660 ms peak widths on average, resulting in a total peak capacity of ∼550 peaks (at unit resolution) and a peak capacity production of ∼90 peaks/min (∼2-fold improvement relative to standard autoinjection with the 1:100 split). This total peak capacity production achieved is equivalent to, or greater than, that currently utilized in metabolomics studies using GC/MS, but with much slower separations, on the order of 40 to 60 min, corresponding to a 5-fold or greater GC/MS analysis throughput rate.
Co-reporter:Brian D. Fitz, Ryan B. Wilson, Brendon A. Parsons, Jamin C. Hoggard, Robert E. Synovec
Journal of Chromatography A 2012 Volume 1266() pp:116-123
Publication Date(Web):30 November 2012
DOI:10.1016/j.chroma.2012.09.096
Peak capacity production is substantially improved for two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC–TOFMS) and applied to the fast separation of a 28 component liquid test mixture, and two complex vapor samples (a 65 component volatile organic compound test mixture, and the headspace of warm ground coffee beans). A high peak capacity is achieved in a short separation time by selecting appropriate experimental conditions based on theoretical modeling of on-column band broadening, and by reducing the off-column band broadening by applying a narrow, concentrated injection pulse onto the primary column using high-speed cryo-focusing injection (HSCFI), referred to as thermal injection. A long, relatively narrow open tubular capillary column (20 m, 100 μm inner diameter (i.d.) with a 0.4 μm film thickness to benefit column capacity) was used as the primary column. The initial flow rate was 2 ml/min (60 cm/s average linear flow velocity) which is slightly below the optimal average linear gas velocity of 83 cm/s, due to the flow rate constraint of the TOFMS vacuum system. The oven temperature programming rate was 30 °C/min. The secondary column (1.8 m, 100 μm i.d. with a 0.1 μm film thickness) provided a relatively high peak capacity separation, concurrent with a significantly shorter modulation period, PM, than commonly applied with the commercial instrument. With this GC × GC–TOFMS instrumental platform, compounds in the 28 component liquid test mixture provided a ∼7 min separation (with a ∼6.5 min separation time window), producing average peak widths of ∼600 ms full width half maximum (FWHM), resulting in a peak capacity on the primary column of ∼400 peaks (at unit resolution). Using a secondary column with a 500 ms PM, average peak widths of ∼20 ms FWHM were achieved, thus providing a peak capacity of 15 peaks on the second dimension. Overall, an ideal orthogonal GC × GC peak capacity of ∼6000 peaks (at unit resolution) was achieved (or a β-corrected orthogonal peak capacity of ∼4400, at an average modulation ratio, MR, of ∼2). This corresponds to an ideal orthogonal peak capacity production of ∼1000 peaks/min (or ∼700 peaks/min, β-corrected). For comparison, standard split/split-less injection techniques with a 1:100 split, when combined with standard GC × GC conditions typically provide a peak capacity production of ∼100 peaks/min, hence the instrumental platform we report provides a ∼7-fold to 10-fold improvement.Highlights► Peak capacity and peak capacity production are significantly improved for GC × GC–TOFMS. ► A peak capacity of ∼6000 was obtained in ∼6 min in a GC × GC–TOFMS separation. ► Primary column peaks were ∼600 ms FWHM and secondary column peaks were ∼20 ms FWHM. ► Cryo-focusing thermal injection was utilized for a narrow injection onto the primary column. ► The instrument was applied to the separation of the headspace of warm, ground coffee beans.
Co-reporter:Karisa M. Pierce, Benjamin Kehimkar, Luke C. Marney, Jamin C. Hoggard, Robert E. Synovec
Journal of Chromatography A 2012 Volume 1255() pp:3-11
Publication Date(Web):14 September 2012
DOI:10.1016/j.chroma.2012.05.050
Comprehensive two-dimensional (2D) separations, such as comprehensive 2D gas chromatography (GC × GC), liquid chromatography (LC × LC), and related instrumental techniques, provide very large and complex data sets. It is often up to the software to assist the analyst in transforming these complex data sets into useful information, and that is precisely where the field of chemometric data analysis plays a pivotal role. Chemometric tools for comprehensive 2D separations are continually being developed and applied as researchers make significant advances in novel state-of-the-art algorithms and software, and as the commercial sector continues to provide user friendly chemometric software. In this review, we build upon previous reviews of this topic, by focusing primarily on advances that have been reported in the past five years. Most of the reports focus on instrumental platforms using GC × GC with either flame ionization detection (FID) or time-of-flight mass spectrometry (TOFMS) detection, or LC × LC with diode array absorbance detection (DAD). The review covers the following general topics: data preprocessing techniques, target analyte techniques, comprehensive nontarget analysis techniques, and software for chemometrics in multidimensional separations.Highlights► Covers chemometric developments in multidimensional separations for 2007–2011. ► Preprocessing: baseline correction, noise reduction, normalization, and alignment. ► Targeted and nontargeted approaches for routine and discovery analyses. ► Software packages are organized for easy reference.
Co-reporter:Song Yang, Jeremy S. Nadeau, Elizabeth M. Humston-Fulmer, Jamin C. Hoggard, Mary E. Lidstrom, Robert E. Synovec
Journal of Chromatography A 2012 1240() pp: 156-164
Publication Date(Web):
DOI:10.1016/j.chroma.2012.03.072
Co-reporter:Ryan B. Wilson, Brian D. Fitz, Brandyn C. Mannion, Tina Lai, Roy K. Olund, Jamin C. Hoggard, Robert E. Synovec
Talanta 2012 Volume 97() pp:9-15
Publication Date(Web):15 August 2012
DOI:10.1016/j.talanta.2012.03.054
In order to maximize peak capacity and detection sensitivity of fast gas chromatography (GC) separations, it is necessary to minimize band broadening, and in particular due to injection since this is often a major contributor. A high-speed cryo-focusing injection (HSCFI) system was constructed to first cryogenically focus analyte compounds in a 6 cm long section of metal MXT column, and second, reinject the focused analytes by rapidly resistively heating the metal column via an in-house built electronic circuit. Since the cryogenically cooled section of column is small (∼750 nl) and the direct resistive heating is fast (∼6000 °C/s), HSCFI is demonstrated to produce an analyte peak with a 6.3 ms width at half height, w1/2. This was achieved using a 1 m long column with a 180 μm inner diameter (i.d.) operated at an absolute head pressure of 55 psi and an oven temperature of 60 °C, with a 10 V pulse applied to the metal column for 50 ms. HSCFI was also used to demonstrate the head space sampling and fast GC analysis of an aqueous solution containing six test analytes (acetone, methanol, ethanol, toluene, chlorobenzene, pentanol). Using Henry’s law constants for each of the analytes, injected mass limits of detection (LODs) were typically in the low pg levels (e.g., 1.2 pg for acetone) for the high speed separation. Finally, to demonstrate the use of HSCFI with a complex sample, a gasoline was separated using a 20 m×100 μm i.d. column and the stock GC oven for temperature programming, which provided a separation time of 200 s and an average peak width at the base of 440 ms resulting in a total peak capacity of 460 peaks (at unit resolution).Highlights► High-speed cryo-focusing injection system made from a short section of MXT column. ► Produced peaks 6.3 ms wide at half height. ► Injected mass limits of detection in the low picogram range. ► Achieved a total peak capacity of 460 peaks during 3 min GC separation.
Co-reporter:W. Christopher Siegler, Brian D. Fitz, Jamin C. Hoggard, and Robert E. Synovec
Analytical Chemistry 2011 Volume 83(Issue 13) pp:5190
Publication Date(Web):May 31, 2011
DOI:10.1021/ac200302b
For complex sample analysis, there is a need for multidimensional chromatographic instrumentation to be able to separate more compounds, often in shorter time frames. This has led to the development of comprehensive two-dimensional chromatographic instrumentation, such as comprehensive two-dimensional gas chromatography (GC × GC). Lately, much of the focus in this field has been on decreasing peak widths and, therefore, increasing peak capacity and peak capacity production. All of these advancements make it possible to analyze more compounds in a shorter amount of time, but the data still need to remain quantitative to address the needs of most applications. In this report, the relationship among the modulation ratio (MR), peak sampling phase (ϕ), retention time variation (ΔtR), and how these parameters relate to quantitative analysis precision via the relative standard deviation (RSD) was studied experimentally using a valve-based GC × GC instrument. A wide range of the number of modulations across the first dimension peak width, that is, a MR range from ∼1 to 10, was examined through maintaining an average first dimension peak width at the base, 1wb of ∼3 s and varying the second dimension separation run time from 300 to 2900 ms. An average RSD of 2.1% was experimentally observed at an average MR of 2, with a corresponding peak capacity production of ∼1200 peaks/min possible. Below this MR the RSD quickly increased. In a long-term study of the quantitative precision at a MR of 2.5, using 126 replicate injections of a test mixture spanning ∼35 h, the RSD averaged 3.0%. The findings have significant implications for optimizing peak capacity production by allowing the use of the longest second dimension run time, while maintaining quantitative precision.
Co-reporter:Jeremy S. Nadeau, Ryan B. Wilson, Brian D. Fitz, Jason T. Reed, Robert E. Synovec
Journal of Chromatography A 2011 Volume 1218(Issue 23) pp:3718-3724
Publication Date(Web):10 June 2011
DOI:10.1016/j.chroma.2011.04.007
A computational approach to partially address the general elution problem (GEP), and better visualize, isothermal gas chromatograms is reported. The theoretical computational approach is developed and applied experimentally. We report a high speed temporally increasing boxcar summation (TIBS) transform that, when applied to the raw isothermal GC data, converts the chromatographic data from the initial time domain (in which the peak widths in isothermal GC increase as a function of their retention factors, k), to a data point based domain in which all peaks have the same peak width in terms of number of points in the final data vector, which aides in preprocessing and data analysis, while minimizing data storage size. By applying the TIBS transform, the resulting GC chromatogram (initially collected isothermally), appears with an x-axis point scale as if it were instrumentally collected using a suitable temperature program. A high speed GC isothermal separation with a test mixture containing 10 compounds had a run time of ∼25 s. The peak at a retention factor k ∼ 0.7 had a peak width of ∼55 ms, while the last eluting peak at k ∼ 89 (i.e., retention time of ∼22 s) had a peak width of ∼2000 ms. Application of the TIBS transform increased the peak height of the last eluting peak 45-fold, and S/N ∼20-fold. All peaks in the transformed test mixture chromatogram had the width of an unretained peak, in terms of number of data points. A simulated chromatogram at unit resolution, studied using the TIBS transform, provided additional insight into the benefits of the algorithm.
Co-reporter:Jeremy S. Nadeau, Ryan B. Wilson, Jamin C. Hoggard, Bob W. Wright, Robert E. Synovec
Journal of Chromatography A 2011 Volume 1218(Issue 50) pp:9091-9101
Publication Date(Web):16 December 2011
DOI:10.1016/j.chroma.2011.10.031
An in-depth study is presented to better understand how data reduction via averaging impacts retention alignment and the subsequent chemometric analysis of data obtained using gas chromatography (GC). We specifically study the use of signal averaging to reduce GC data, retention time alignment to correct run-to-run retention shifting, and principal component analysis (PCA) to classify chromatographic separations of diesel samples by sample class. Diesel samples were selected because they provide sufficient complexity to study the impact of data reduction on the data analysis strategies. The data reduction process reduces the data sampling ratio, SR, which is defined as the number of data points across a given chromatographic peak width (i.e., the four standard deviation peak width). Ultimately, sufficient data reduction causes the chromatographic resolution to decrease, however with minimal loss of chemical information via the PCA. Using PCA, the degree of class separation (DCS) is used as a quantitative metric. Three “Paths” of analysis (denoted A–C) are compared to each other in the context of a “benchmark” method to study the impact of the data sampling ratio on preserving chemical information, which is defined by the DCS quantitative metric. The benchmark method is simply aligning data and applying PCA, without data reduction. Path A applies data alignment to collected data, then data reduction, and finally PCA. Path B applies data reduction to collected data, and then data alignment, and finally PCA. The optimized path, namely Path C, is created from Paths A and B, whereby collected data are initially reduced to fewer data points (smaller SR), then aligned, and then further reduced to even fewer points and finally analyzed with PCA to provide the DCS metric. Overall, following Path C, one can successfully and efficiently classify chromatographic data by reducing to a SR of ∼15 before alignment, and then reducing down to SR of ∼2 before performing PCA. Indeed, following Path C, results from an average of 15 different column length-with-temperature ramp rate combinations spanning a broad range of separation conditions resulted in only a ∼15% loss in classification capability (via PCA) when the loss in chromatographic resolution was ∼36%.Highlights► Data reduction by averaging impacts alignment and chemometric analysis. ► Averaging data to 15 points per peak prior to alignment is important. ► Averaging aligned data to 2 points per peak before PCA is acceptable. ► Significant implications for minimizing computational time are provided.
Co-reporter:Ryan B. Wilson, W. Christopher Siegler, Jamin C. Hoggard, Brian D. Fitz, Jeremy S. Nadeau, Robert E. Synovec
Journal of Chromatography A 2011 Volume 1218(Issue 21) pp:3130-3139
Publication Date(Web):27 May 2011
DOI:10.1016/j.chroma.2010.12.108
By taking into consideration band broadening theory and using those results to select experimental conditions, and also by reducing the injection pulse width, peak capacity production (i.e., peak capacity per separation time) is substantially improved for one dimensional (1D-GC) and comprehensive two dimensional (GC × GC) gas chromatography. A theoretical framework for determining the optimal linear gas velocity (the linear gas velocity producing the minimum H), from experimental parameters provides an in-depth understanding of the potential for GC separations in the absence of extra-column band broadening. The extra-column band broadening is referred to herein as off-column band broadening since it is additional band broadening not due to the on-column separation processes. The theory provides the basis to experimentally evaluate and improve temperature programmed 1D-GC separations, but in order to do so with a commercial 1D-GC instrument platform, off-column band broadening from injection and detection needed to be significantly reduced. Specifically for injection, a resistively heated transfer line is coupled to a high-speed diaphragm valve to provide a suitable injection pulse width (referred to herein as modified injection). Additionally, flame ionization detection (FID) was modified to provide a data collection rate of 5 kHz. The use of long, relatively narrow open tubular capillary columns and a 40 °C/min programming rate were explored for 1D-GC, specifically a 40 m, 180 μm i.d. capillary column operated at or above the optimal average linear gas velocity. Injection using standard auto-injection with a 1:400 split resulted in an average peak width of ∼1.5 s, hence a peak capacity production of 40 peaks/min. In contrast, use of modified injection produced ∼500 ms peak widths for 1D-GC, i.e., a peak capacity production of 120 peaks/min (a 3-fold improvement over standard auto-injection). Implementation of modified injection resulted in retention time, peak width, peak height, and peak area average RSD%’s of 0.006, 0.8, 3.4, and 4.0%, respectively. Modified injection onto the first column of a GC × GC coupled with another high-speed valve injection onto the second column produced an instrument with high peak capacity production (500–800 peaks/min), ∼5-fold to 8-fold higher than typically reported for GC × GC.
Co-reporter:Thomas I. Dearing, Jeremy S. Nadeau, Brian G. Rohrback, L. Scott Ramos, Robert E. Synovec
Talanta 2011 Volume 83(Issue 3) pp:738-743
Publication Date(Web):15 January 2011
DOI:10.1016/j.talanta.2010.10.026
An improved method for real-time selection of the target for the alignment of gas chromatographic data is described. Further outlined is a simple method to determine the accuracy of the alignment procedure. The target selection method proposed uses a moving window of aligned chromatograms to generate a target, herein referred to as the window target method (WTM). The WTM was initially tested using a series of 100 simulated chromatograms, and additionally evaluated using a series of 55 diesel fuel gas chromatograms obtained with four fuel samples. The WTM was evaluated via a comparison to a related method (the nearest neighbor method (NNM)). The results using the WTM with simulated chromatograms showed a significant improvement in the correlation coefficient and the accuracy of alignment when compared to the alignments performed using the NNM. A significant improvement in real-time alignment accuracy, as assessed by a correlation coefficient metric, was achieved with the WTM (starting at ∼1.0 and declining to only ∼0.985 for the 100th sample), relative to the NNM (starting at ∼1.0 and declining to ∼0.4 for the 100th sample) for the simulated chromatogram study. The results determined when using the WTM with the diesel fuels also showed an improvement in correlation coefficient and accuracy of the within-class alignments as compared to the results obtained from the NNM. In practice, the WTM could be applied to the real-time analysis of process and feedstock industrial streams to enable real-time decision making from the more precisely aligned chromatographic data.
Co-reporter:Elizabeth M. Humston;Kenneth M. Dombek
Analytical and Bioanalytical Chemistry 2011 Volume 401( Issue 8) pp:2387-2402
Publication Date(Web):2011 November
DOI:10.1007/s00216-011-4800-2
The AMP-activated protein kinase in yeast, Snf1, coordinates expression and activity of numerous intracellular signaling and developmental pathways, including those regulating cellular differentiation, response to stress, meiosis, autophagy, and the diauxic transition. Snf1 phosphorylates metabolic enzymes and transcription factors to change cellular physiology and metabolism. Adr1 and Cat8, transcription factors that activate gene expression after the diauxic transition, are regulated by Snf1; Cat8 through direct phosphorylation and Adr1 by dephosphorylation in a Snf1-dependent manner. Adr1 and Cat8 coordinately regulate numerous genes encoding enzymes of gluconeogenesis, the glyoxylate cycle, β-oxidation of fatty acids, and the utilization of alternative fermentable sugars and nonfermentable substrates. To determine the roles of Adr1, Cat8, and Snf1 in metabolism, two-dimensional gas chromatography coupled to time-of-flight mass spectrometry and liquid chromatography coupled to tandem mass spectrometry were used to identify metabolites whose levels change after the diauxic transition in wild-type-, ADR1-, CAT8-, and SNF1-deficient yeast. A discovery-based approach to data analysis utilized chemometric algorithms to identify, quantify, and compare 63 unique metabolites between wild type, adr1∆, cat8∆, adr1∆cat8∆, and snf1∆ strains. The primary metabolites found to differ were those of gluconeogenesis, the glyoxylate and tricarboxylic acid cycles, and amino acid metabolism. In general, good agreement was observed between the levels of metabolites derived from these pathways and the levels of transcripts from the same strains, suggesting that transcriptional control plays a major role in regulating the levels of metabolites after the diauxic transition.
Co-reporter:Elizabeth M. Humston, Jamin C. Hoggard and Robert E. Synovec
Analytical Chemistry 2010 Volume 82(Issue 1) pp:41
Publication Date(Web):December 4, 2009
DOI:10.1021/ac902184b
Akin to the standard addition method requiring only a single chromatographic injection, a robust isotope dilution mass spectrometry method is described. The 13C labeled analyte at known concentration serves as the standard to quantify the unlabeled target analyte. Two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-TOFMS) provides a combined 12C and 13C analyte peak as part of the third order data cube. This combined peak can be isolated from interfering compounds and noise based on the “third order advantage” with parallel factor analysis (PARAFAC). The combined mass spectra are then mathematically resolved using classical least squares (CLS) providing a 12C/13C ratio, thus absolute amounts of 12C and 13C. Good agreement between the prepared and determined concentration ratios for test analytes was achieved with further demonstration to real-world samples.
Co-reporter:Elizabeth M. Humston, Joshua D. Knowles, Andrew McShea, Robert E. Synovec
Journal of Chromatography A 2010 Volume 1217(Issue 12) pp:1963-1970
Publication Date(Web):19 March 2010
DOI:10.1016/j.chroma.2010.01.069
Quality control of cacao beans is a significant issue in the chocolate industry. In this report, we describe how moisture damage to cacao beans alters the volatile chemical signature of the beans in a way that can be tracked quantitatively over time. The chemical signature of the beans is monitored via sampling the headspace of the vapor above a given bean sample. Headspace vapor sampled with solid-phase micro-extraction (SPME) was detected and analyzed with comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC × GC–TOFMS). Cacao beans from six geographical origins (Costa Rica, Ghana, Ivory Coast, Venezuela, Ecuador, and Panama) were analyzed. Twenty-nine analytes that change in concentration levels via the time-dependent moisture damage process were measured using chemometric software. Biomarker analytes that were independent of geographical origin were found. Furthermore, prediction algorithms were used to demonstrate that moisture damage could be verified before there were visible signs of mold by analyzing subsets of the 29 analytes. Thus, a quantitative approach to quality screening related to the identification of moisture damage in the absence of visible mold is presented.
Co-reporter:Laura R. Snyder, Jamin C. Hoggard, Thomas J. Montine, Robert E. Synovec
Journal of Chromatography A 2010 Volume 1217(Issue 27) pp:4639-4647
Publication Date(Web):2 July 2010
DOI:10.1016/j.chroma.2010.04.065
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.
Co-reporter:W. Christopher Siegler, Jeffery A. Crank, Daniel W. Armstrong, Robert E. Synovec
Journal of Chromatography A 2010 Volume 1217(Issue 18) pp:3144-3149
Publication Date(Web):30 April 2010
DOI:10.1016/j.chroma.2010.02.082
Recent advances in improving the selectivity and performance for a comprehensive, three-dimensional (3D) gas chromatograph (GC3) instrument are described. With GC3, two six-port diaphragm valves are utilized as the interfaces between three, in-series capillary columns housed in a standard GC instrument fitted with a high data acquisition rate flame ionization detector (FID). Modulation periods for sampling from one column to the next are set so that sufficient slices (i.e., modulations) are acquired by the subsequent dimension resulting in comprehensive data. We present GC3 instrumentation with significantly higher 3D peak capacity than previously reported. An average peak capacity production (i.e., per time) of 180 resolved peaks per minute was experimentally achieved for three representative analytes in a 3D diesel sample separation. This peak capacity production is about 4 times higher than our previous report. We also demonstrate the significant benefit of the added chemical selectivity of the three column GC3 instrument relative to a two column GC × GC instrument, in which one of the three columns is a triflate ionic liquid stationary phase column with a high selectivity for phosphonated compounds (i.e., di-methyl-methyl phosphonate, di-ethyl-methyl phosphonate and di-isopropyl-methyl phosphonate). Using all three separation dimensions, the 2D separation fingerprint of a diesel sample is simultaneously obtained along with selective information regarding the phosphonated compounds in the diesel samples in the additional dimension.
Co-reporter:Jeremy S. Nadeau, Bob W. Wright, Robert E. Synovec
Talanta 2010 Volume 81(1–2) pp:120-128
Publication Date(Web):15 April 2010
DOI:10.1016/j.talanta.2009.11.046
A critical comparison of methods for correcting severely retention time shifted gas chromatography–mass spectrometry (GC–MS) data is presented. The method reported herein is an adaptation to the piecewise alignment algorithm to quickly align severely shifted one-dimensional (1D) total ion current (TIC) data, then applying these shifts to broadly align all mass channels throughout the separation, referred to as a TIC shift function (SF). The maximum shift varied from (−) 5 s in the beginning of the chromatographic separation to (+) 20 s toward the end of the separation, equivalent to a maximum shift of over 5 peak widths. Implementing the TIC shift function (TIC SF) prior to Fisher Ratio (F-Ratio) feature selection and then principal component analysis (PCA) was found to be a viable approach to classify complex chromatograms, that in this study were obtained from GC–MS separations of three gasoline samples serving as complex test mixtures, referred to as types C, M and S. The reported alignment algorithm via the TIC SF approach corrects for large dynamic shifting in the data as well as subtle peak-to-peak shifts. The benefits of the overall TIC SF alignment and feature selection approach were quantified using the degree-of-class separation (DCS) metric of the PCA scores plots using the type C and M samples, since they were the most similar, and thus the most challenging samples to properly classify. The DCS values showed an increase from an initial value of essentially zero for the unaligned GC-TIC data to a value of 7.9 following alignment; however, the DCS was unchanged by feature selection using F-Ratios for the GC-TIC data. The full mass spectral data provided an increase to a final DCS of 13.7 after alignment and two-dimensional (2D) F-Ratio feature selection.
Co-reporter:Elizabeth M. Humston;Yan Zhang;Gregory F. Brabeck;Andrew McShea
Journal of Separation Science 2009 Volume 32( Issue 13) pp:2289-2295
Publication Date(Web):
DOI:10.1002/jssc.200900143
Abstract
A method to analyze volatile compounds from cacao beans has been developed and evaluated. The method utilizes solid phase micro extraction (SPME) sampling followed by comprehensive 2-D (GC×GC) coupled with TOFMS. For the SPME procedure, a polydimethyl siloxane/divinyl benzene (PDMS/DVB) fiber was implemented. Cacao beans from four geographical origins were studied under two storage conditions, either dry or high moisture. A given cacao bean sample was sealed in a SPME vial and heated for 15 min. Extraction temperatures of 45, 60, 80, and 100°C were analyzed and an optimal extraction temperature of 60°C was determined. Many peaks were found to change as a function of storage conditions with Fisher Ratio analysis. Four representative compounds were identified and quantified (on a relative basis): acetic acid, nonanal, tetramethyl pyrazine, and trimethyl pyrazine. Acetic acid and nonanal were elevated in samples without evident mold on the bean surface, while the two pyrazines were elevated when mold was evident on the bean surface. The results for these comparisons, indicate that metabolism at the bean surface plays a role in the concentration of analytes, and can be readily determined using this analytical technology and methodology.
Co-reporter:Jamin C. Hoggard;W. Christopher Siegler
Journal of Chemometrics 2009 Volume 23( Issue 7-8) pp:421-431
Publication Date(Web):
DOI:10.1002/cem.1239
Abstract
We have previously developed automated PARAFAC methods for resolving peaks from small subsections of data, obtained using comprehensive multidimensional gas chromatography with mass spectral detection (GC × GC–TOFMS). Herein, we build upon those previous methods and present a new method for resolving peaks across much larger sections or even entire GC × GC–TOFMS chromatograms using PARAFAC in an automated fashion. In addition, the method presented is demonstrated on three GC × GC–TOFMS data sets: (1) a complete chromatogram of a test mixture of 32 compounds, (2) several compounds spiked into a diesel sample at two known concentrations and (3) a large section of the chromatogram of the headspace of a urine sample collected by solid phase microextraction (SPME), i.e. containing volatile metabolites. The results of these analyses show that the presented method resolves peaks (including overlapping peaks) and provides useful quantitative and identification information as long as some care is taken in the selection of parameters (such as the size of subsections to be analyzed individually by PARAFAC). Analysis time using PARAFAC remains a challenge, but a technique for reducing the amount of time is demonstrated and future possibilities for greatly reducing the analysis time are discussed. Copyright © 2009 John Wiley & Sons, Ltd.
Co-reporter:Vanessa R. Reid, Michael Stadermann, Olgica Bakajin, Robert E. Synovec
Talanta 2009 Volume 77(Issue 4) pp:1420-1425
Publication Date(Web):15 February 2009
DOI:10.1016/j.talanta.2008.09.023
A new growth recipe for producing carbon nanotubes (CNTs) combined with a new bonding technique was implemented in a microfabricated gas chromatography (micro-GC) chip. Specifically, the micro-GC chip contained a 30-cm (length) microfabricated channel with a 50 μm × 50 μm square cross-section. A CNT stationary phase “mat” was grown on the bottom of the separation channel prior to the chip bonding. Injections onto the micro-GC chip were made using a previously reported high-speed diaphragm valve technique. A FID was used for detection with a high-speed electrometer board. All together, the result was a highly efficiency, temperature programmable (via low thermal mass, rapid on-chip resistive heating) micro-GC chip. In general, the newly designed micro-GC chip can be operated at significantly lower temperature and pressure than our previously reported micro-GC chip, while producing excellent chemical separations. Scanning electron microscopy (SEM) images show a relatively thin and uniform mat of nanotubes with a thickness of ∼800 nm inside the channel. The stationary phase was further characterized using Raman spectroscopy. The uniformity of the stationary phase resulted in better separation efficiency and peak symmetry (as compared to our previous report) in the separation of a mixture of five n-alkanes (n-hexane, n-octane, n-nonane, n-decane and n-undecane). The on-chip resistive heater employing a temperature programming rate of 26 °C/s produced a peak capacity of eight within a 1.5-s time window.
Co-reporter:Elizabeth M. Humston, Kenneth M. Dombek, Jamin C. Hoggard, Elton T. Young and Robert E. Synovec
Analytical Chemistry 2008 Volume 80(Issue 21) pp:8002
Publication Date(Web):October 1, 2008
DOI:10.1021/ac800998j
The effect of sampling time in the context of growth conditions on a dynamic metabolic system was investigated in order to assess to what extent a single sampling time may be sufficient for general application, as well as to determine if useful kinetic information could be obtained. A wild type yeast strain (W) was compared to a snf1Δ mutant yeast strain (S) grown in high-glucose medium (R) and in low-glucose medium containing ethanol (DR). Under these growth conditions, different metabolic pathways for utilizing the different carbon sources are expected to be active. Thus, changes in metabolite levels relating to the carbon source in the growth medium were anticipated. Furthermore, the Snf1 protein kinase complex is required to adapt cellular metabolism from fermentative R conditions to oxidative DR conditions. So, differences in intracellular metabolite levels between the W and S yeast strains were also anticipated. Cell extracts were collected at four time points (0.5, 2, 4, 6 h) after shifting half of the cells from R to DR conditions, resulting in 16 sample classes (WR, WDR, SR, SDR) × (0.5, 2, 4, 6 h). The experimental design provided time course data, so temporal dependencies could be monitored in addition to carbon source and strain dependencies. Comprehensive two-dimensional (2D) gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-TOFMS) was used with discovery-based data mining algorithms (Anal. Chem. 2006, 78, 5068–5075 (ref 1); J. Chromatogr., A 2008, 1186, 401–411 (ref 2)) to locate regions within the 2D chromatograms (i.e., metabolites) that provided chemical selectivity between the 16 sample classes. These regions were mathematically resolved using parallel factor analysis to positively identify the metabolites and to acquire quantitative results. With these tools, 51 unique metabolites were identified and quantified. Various time course patterns emerged from these data, and principal component analysis (PCA) was utilized as a comparison tool to determine the sources of variance between these 51 metabolites. The effect of sampling time was investigated with separate PCA analyses using various subsets of the data. PCA utilizing all of the time course data, averaged time course data, and each individual time point data set independently were performed to discern the differences. For the yeast strains examined in the current study, data collection at either 4 or 6 h provided information comparable to averaged time course data, albeit with a few metabolites missing using a single sampling time point.
Co-reporter:Jamin C. Hoggard and Robert E. Synovec
Analytical Chemistry 2008 Volume 80(Issue 17) pp:6677
Publication Date(Web):August 2, 2008
DOI:10.1021/ac800624e
We previously reported a method for the automated (objective) selection of a PARAFAC model having an appropriate number of factors for mathematical resolution of signal from a target analyte in GC × GC-TOFMS data (i.e., for an analysis in which the identity of the analyte is known a priori). While the previous target method has been successfully applied in several studies, the target method requires that the identity of the analyte be known. Also, multiple applications of the target method are required in cases where several analytes of interest are present in a single subsection of the chromatogram. Thus, having to know the analyte identity a priori restricts the applicability of the automated implementation of PARAFAC. The method presented in this report generalizes the previous method to allow analysis of one or more nontarget analyte signals in a subsection of a GC × GC-TOFMS chromatogram (i.e., for analyses when identities of analyte and interferences are not known a priori), thereby addressing and overcoming the limitations of the target method. Herein, we put the nontarget analyte PARAFAC method into theoretical context and illustrate the mechanics of the method using simulated data. We use real experimental GC × GC-TOFMS data to demonstrate the broad applicability of the method, with various analysis situations selected to illustrate challenging chemical analysis scenarios.
Co-reporter:Rachel E. Mohler, Benjamin P. Tu, Kenneth M. Dombek, Jamin C. Hoggard, Elton T. Young, Robert E. Synovec
Journal of Chromatography A 2008 Volume 1186(1–2) pp:401-411
Publication Date(Web):4 April 2008
DOI:10.1016/j.chroma.2007.10.063
A yeast metabolome exhibiting oscillatory behavior was analyzed using comprehensive two-dimensional gas chromatography–time-of-flight-mass spectrometry (GC × GC–TOF-MS) and in-house developed data analysis software methodology, referred to as a signal ratio method (Sratio 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 Sratio 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 Sratio information (which serves as a rapid screening procedure to find the cycling metabolites while excluding peaks that do not cycle). The Sratio 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.
Co-reporter:Vanessa R. Reid;Jeffery A. Crank;Daniel W. Armstrong
Journal of Separation Science 2008 Volume 31( Issue 19) pp:3429-3436
Publication Date(Web):
DOI:10.1002/jssc.200800251
Abstract
A novel triflate (trifluoromethylsulfonate) ionic liquid (IL) thin film (0.08 μm) stationary phase was implemented for use within the second column of a comprehensive GC×GC configuration. The first column in the configuration had a 5% phenyl/95% dimethyl polysiloxane (DMPS) stationary phase with a 0.4 μm film. The DMPS×IL column configuration was used to separate a mixture of 32 compounds of various chemical functional classes. The GC×GC results for the IL column were compared with a commercially available polar column (with a 0.1 μm PEG stationary phase film) used as the second column instead. Additional studies focused on the rapid and selective separation of four phosphorous–oxygen (P–O) containing compounds from the 32-compound matrix: dimethyl methylphosphonate (DMMP), diethyl methylphosphonate (DEMP), diisopropyl methylphosphonate (DIMP), and triethyl phosphate (TEP). van't Hoff plots (plots of ln k vs. 1/T) demonstrated the difference in retention between the P–O containing compounds (with DMMP reported in detail) and other classes of compounds (i. e., 2-pentanol and n-dodecane as representative) using either the IL column or the commercial PEG column. The selectivity (α) of the triflate IL column and the commercially available PEG column were also compared. The IL column provided significantly larger selectivities between DMMP and the other two compounds (2-pentanol and n-dodecane) than the commercial PEG column. The α for DMMP relative to n-dodecane was 3.0-fold greater for the triflate IL column, and the α for DMMP relative to 2-pentanol was 1.7-fold greater for the triflate IL column than for the PEG column.
Co-reporter:Vanessa R. Reid, Robert E. Synovec
Talanta 2008 Volume 76(Issue 4) pp:703-717
Publication Date(Web):15 August 2008
DOI:10.1016/j.talanta.2008.05.012
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 ∼1 ms is readily achievable in GC, when extra-column band broadening is eliminated.
Co-reporter:Rachel E. Mohler, Kenneth M. Dombek, Jamin C. Hoggard, Karisa M. Pierce, Elton T. Young and Robert E. Synovec
Analyst 2007 vol. 132(Issue 8) pp:756-767
Publication Date(Web):22 May 2007
DOI:10.1039/B700061H
The first extensive study of yeast metabolite GC×GC–TOFMS data from cells grown under fermenting, R, and respiring, DR, conditions is reported. In this study, recently developed chemometric software for use with three-dimensional instrumentation data was implemented, using a statistically-based Fisher ratio method. The Fisher ratio method is fully automated and will rapidly reduce the data to pinpoint two-dimensional chromatographic peaks differentiating sample types while utilizing all the mass channels. The effect of lowering the Fisher ratio threshold on peak identification was studied. At the lowest threshold (just above the noise level), 73 metabolite peaks were identified, nearly three-fold greater than the number of previously reported metabolite peaks identified (26). In addition to the 73 identified metabolites, 81 unknown metabolites were also located. A Parallel Factor Analysis graphical user interface (PARAFAC GUI) was applied to selected mass channels to obtain a concentration ratio, for each metabolite under the two growth conditions. Of the 73 known metabolites identified by the Fisher ratio method, 54 were statistically changing to the 95% confidence limit between the DR and R conditions according to the rigorous Student's t-test. PARAFAC determined the concentration ratio and provided a fully-deconvoluted (i.e. mathematically resolved) mass spectrum for each of the metabolites. The combination of the Fisher ratio method with the PARAFAC GUI provides high-throughput software for discovery-based metabolomics research, and is novel for GC×GC–TOFMS data due to the use of the entire data set in the analysis (640 MB × 70 runs, double precision floating point).
Co-reporter:Karisa M. Pierce, Bob W. Wright, Robert E. Synovec
Journal of Chromatography A 2007 Volume 1141(Issue 1) pp:106-116
Publication Date(Web):2 February 2007
DOI:10.1016/j.chroma.2006.11.101
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%.
Co-reporter:Elizabeth M. Humston, Adam D. McBrady, Maribel Valero, Robert E. Synovec
Talanta 2007 Volume 73(Issue 2) pp:287-295
Publication Date(Web):15 September 2007
DOI:10.1016/j.talanta.2007.03.040
Non-aqueous size exclusion chromatography (SEC) of polystyrenes (as model analytes) is examined using the microscale molar mass sensor (μ-MMS) for detection. The μ-MMS is combined with SEC to demonstrate this simultaneously universal and molar mass selective detection method for polymer characterization. The μ-MMS is based on measuring the refractive index gradient (RIG) at two positions (upstream and downstream) within a T-shaped microfluidic channel. The RIG is produced from a sample stream (eluting analytes in the mobile phase) merging with a mobile phase stream (mobile phase only). The magnitude of the RIG is measured as a probe beam deflection angle and is related to analyte diffusion coefficient, the time allowed for analyte diffusion from the sample stream toward the mobile phase stream, and the bulk phase analyte refractive index difference relative to the mobile phase. Thus, two deflection angles are measured simultaneously, the upstream angle and the downstream angle. An angle ratio is calculated by dividing the downstream angle by the upstream angle. The μ-MMS was found to extend the useful molar mass calibration range of the SEC system (nominally limited by the total exclusion and total permeation regions from ∼100,000 g/mol to ∼800 g/mol), to a range of 3,114,000–162 g/mol. The injected concentration LOD (based on 3 s statistics) was 2 ppm for the upstream detection position. The point-by-point time-dependent ratio, termed a ‘ratiogram’, is demonstrated for resolved and overlapped peaks. Within detector band broadening produces some anomalies in the ratiogram shapes, but with highly overlapped distributions of peaks this problem is diminished. Ratiogram plots are converted to molar mass as a function of time, demonstrating the utility of SEC/μ-MMS to examine a complex polymer mixture.
Co-reporter:Adam D. McBrady, Rattikan Chantiwas, Ana Kristine Torgerson, Kate Grudpan, Robert E. Synovec
Analytica Chimica Acta 2006 Volume 575(Issue 2) pp:151-158
Publication Date(Web):11 August 2006
DOI:10.1016/j.aca.2006.05.083
The H-Sensor reported herein is a micro-fluidic device compatible with flow injection analysis (FIA) and high performance liquid chromatography (HPLC). The device detects analytes at two separate off-chip absorbance flow cells, providing two simultaneous absorbance measurements. The ratio of these two absorbance signals contains analyte diffusion coefficient information. A theoretical model for the sensing mechanism is presented. The model relates the signal Ratio to analyte diffusion coefficient. The model is qualitatively evaluated by comparing theoretical and experimental signal Ratio values. Experimental signal Ratios were collected via FIA for a variety of analytes, including sodium azide, benzoic acid, amino acids, peptides, and proteins. Measuring absorbance at multiple wavelengths provides higher order data allowing the analyte signals from mixtures to be deconvolved via classical least squares (CLS). As a result of the H-Sensor providing two simultaneous signals as a function of time for each sample injection, two simulated second-order HPLC chromatograms were generated using experimental H-Sensor data. The chemometric deconvolution method referred to as the generalized rank annihilation method (GRAM) was used to demonstrate chromatographic and spectroscopic deconvolution. GRAM also provides the signal Ratio value, therefore simultaneously obtaining the analyte diffusion coefficient information during deconvolution. The two chromatograms successfully serve as the standard and unknown for the GRAM deconvolution. GRAM was evaluated on chromatograms at various chromatographic resolutions. GRAM was found to function to a chromatographic resolution at and above 0.25 with a percent quantitative error of less then 10%.
Co-reporter:Nathanial E. Watson, Matthew M. VanWingerden, Karisa M. Pierce, Bob W. Wright, Robert E. Synovec
Journal of Chromatography A 2006 Volume 1129(Issue 1) pp:111-118
Publication Date(Web):29 September 2006
DOI:10.1016/j.chroma.2006.06.087
A useful methodology is introduced for the analysis of data obtained via gas chromatography with mass spectrometry (GC–MS) utilizing a complete mass spectrum at each retention time interval in which a mass spectrum was collected. Principal component analysis (PCA) with preprocessing by both piecewise retention time alignment and analysis of variance (ANOVA) feature selection is applied to all mass channels collected. The methodology involves concatenating all concurrently measured individual m/z chromatograms from m/z 20 to 120 for each GC–MS separation into a row vector. All of the sample row vectors are incorporated into a matrix where each row is a sample vector. This matrix is piecewise aligned and reduced by ANOVA feature selection. Application of the preprocessing steps (retention time alignment and feature selection) to all mass channels collected during the chromatographic separation allows considerably more selective chemical information to be incorporated in the PCA classification, and is the primary novelty of the report. This methodology is objective and requires no knowledge of the specific analytes of interest, as in selective ion monitoring (SIM), and does not restrict the mass spectral data used, as in both SIM and total ion current (TIC) methods. Significantly, the methodology allows for the classification of data with low resolution in the chromatographic dimension because of the added selectivity from the complete mass spectral dimension. This allows for the successful classification of data over significantly decreased chromatographic separation times, since high-speed separations can be employed. The methodology is demonstrated through the analysis of a set of four differing gasoline samples that serve as model complex samples. For comparison, the gasoline samples are analyzed by GC–MS over both 10-min and 10-s separation times. The successfully classified 10-min GC–MS TIC data served as the benchmark analysis to compare to the 10-s data. When only alignment and feature selection was applied to the 10-s gasoline separations using GC–MS TIC data, PCA failed. PCA was successful for 10-s gasoline separations when the methodology was applied with all the m/z information. With ANOVA feature selection, chromatographic regions with Fisher ratios greater than 1500 were retained in a new matrix and subjected to PCA yielding successful classification for the 10-s separations.
Co-reporter:Bethany A. Staggemeier, Terry O. Collier, Bryan J. Prazen, Robert E. Synovec
Analytica Chimica Acta 2005 Volume 534(Issue 1) pp:79-87
Publication Date(Web):4 April 2005
DOI:10.1016/j.aca.2004.11.022
A dynamic surface tension detector (DSTD) was used to examine the molecular diffusion and surface adsorption characteristics of surface-active analytes as a function of solution viscosity. Dynamic surface tension is determined by measuring the differential pressure across the air/liquid interface of repeatedly growing and detaching drops. Continuous surface tension measurement throughout the entire drop growth is achieved for each eluting drop (at a rate of 30 drops/min for 2 μl drops), providing insight into the kinetic behavior of molecular diffusion and orientation processes at the air/liquid interface. Three-dimensional data are obtained through a calibration procedure previously developed, but extended herein for viscous solutions, with surface tension first converted to surface pressure, which is plotted as a function of elution time axis versus drop time axis. Thus, an analyte that lowers the surface tension results in an increase in surface pressure. The calibration procedure derived for the pressure-based DSTD was successfully extended and implemented in this report to experimentally determine standard surface pressures in solutions of varied viscosity. Analysis of analytes in viscous solution was performed at low analyte concentration, where the observed analyte surface activity indicates that the surface concentration is at or near equilibrium when in a water mobile phase (viscosity of 1.0 Cp). Two surface-active analytes, sodium dodecyl sulfate (SDS) and polyethylene glycol (MW 1470 g/mol, PEG 1470), were analyzed in solutions ranging from 0 to 60% (v/v) glycerol in water, corresponding to a viscosity range of 1.0–15.0 Cp. Finally, the diffusion-limited surface activity of SDS and PEG 1470 were observed in viscous solution, whereby an increase in viscosity resulted in a decreased surface pressure early in drop growth. The dynamic surface pressure results reported for SDS and PEG 1470 are found to correlate with solution viscosity and analyte diffusion coefficient via the Stokes–Einstein equation.
Co-reporter:Karisa M. Pierce, Janiece L. Hope, Kevin J. Johnson, Bob W. Wright, Robert E. Synovec
Journal of Chromatography A 2005 Volume 1096(1–2) pp:101-110
Publication Date(Web):25 November 2005
DOI:10.1016/j.chroma.2005.04.078
A fast and objective chemometric classification method is developed and applied to the analysis of gas chromatography (GC) data from five commercial gasoline samples. The gasoline samples serve as model mixtures, whereas the focus is on the development and demonstration of the classification method. The method is based on objective retention time alignment (referred to as piecewise alignment) coupled with analysis of variance (ANOVA) feature selection prior to classification by principal component analysis (PCA) using optimal parameters. The degree-of-class-separation is used as a metric to objectively optimize the alignment and feature selection parameters using a suitable training set thereby reducing user subjectivity, as well as to indicate the success of the PCA clustering and classification. The degree-of-class-separation is calculated using Euclidean distances between the PCA scores of a subset of the replicate runs from two of the five fuel types, i.e., the training set. The unaligned training set that was directly submitted to PCA had a low degree-of-class-separation (0.4), and the PCA scores plot for the raw training set combined with the raw test set failed to correctly cluster the five sample types. After submitting the training set to piecewise alignment, the degree-of-class-separation increased (1.2), but when the same alignment parameters were applied to the training set combined with the test set, the scores plot clustering still did not yield five distinct groups. Applying feature selection to the unaligned training set increased the degree-of-class-separation (4.8), but chemical variations were still obscured by retention time variation and when the same feature selection conditions were used for the training set combined with the test set, only one of the five fuels was clustered correctly. However, piecewise alignment coupled with feature selection yielded a reasonably optimal degree-of-class-separation for the training set (9.2), and when the same alignment and ANOVA parameters were applied to the training set combined with the test set, the PCA scores plot correctly classified the gasoline fingerprints into five distinct clusters.
Co-reporter:Narong Lenghor, Bethany A. Staggemeier, Mazen L. Hamad, Yuthapong Udnan, Sumalee Tanikkul, Jaroon Jakmunee, Kate Grudpan, Bryan J. Prazen, Robert E. Synovec
Talanta 2005 Volume 65(Issue 3) pp:722-729
Publication Date(Web):15 February 2005
DOI:10.1016/j.talanta.2004.07.040
Design and development of a dynamic interfacial pressure detector (DIPD) is reported. The DIPD measures the differential pressure as a function of time across the liquid–liquid interface of organic liquid drops (i.e., n-hexane) that repeatedly grow in water at the end of a capillary tip. Using a calibration technique based on the Young–Laplace equation, the differential pressure signal is converted, in real-time, to a relative interfacial pressure. This allows the DIPD to monitor the interfacial tension of surface active species at liquid–liquid interfaces in flow-based analytical techniques, such as flow injection analysis (FIA), sequential injection analysis (SIA) and high performance liquid chromatography (HPLC). The DIPD is similar in principle to the dynamic surface tension detector (DSTD), which monitors the surface tension at the air–liquid interface. In this report, the interfacial pressure at the hexane–water interface was monitored as analytes in the hexane phase diffused to and arranged at the hexane–water interface. The DIPD was combined with FIA to analytically measure the interfacial properties of cholesterol and Brij®30 at the hexane–water interface. Results show that both cholesterol and Brij®30 exhibit a dynamic interfacial pressure signal during hexane drop growth. A calibration curve demonstrates that the relative interfacial pressure of cholesterol in hexane increases as the cholesterol concentration increases from 100 to 10,000 μg ml−1. An example of the utility of the DIPD as a selective detector for a chromatographic separation of interface-active species is also presented in the analysis of cholesterol in egg yolk by normal-phase HPLC-DIPD.
Co-reporter:Amanda E. Sinha, Janiece L. Hope, Bryan J. Prazen, Carlos G. Fraga, Erik J. Nilsson, Robert E. Synovec
Journal of Chromatography A 2004 Volume 1056(1–2) pp:145-154
Publication Date(Web):12 November 2004
DOI:10.1016/j.chroma.2004.06.110
Two-dimensional gas chromatography (GC × GC) coupled to time-of-flight mass spectrometry (TOFMS) [GC × 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 × 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 × 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 × 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 × GC–TOFMS followed by TLD/PARAFAC is demonstrated for a plant metabolite sample. A region of GC × 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.
Co-reporter:Gwen M Gross, Jay W Grate, Robert E Synovec
Journal of Chromatography A 2004 Volume 1029(1–2) pp:185-192
Publication Date(Web):12 March 2004
DOI:10.1016/j.chroma.2003.12.058
The application of a dodecanethiol monolayer-protected gold nanoparticle (MPN) stationary phase within a microchannel environment was explored using a square capillary column as a model for high-speed, microfabricated gas chromatography (μGC). Successful deposition and evaluation of a dodecanethiol MPN phase within a 1.3 m long, μm square capillary is reported. The thickness of the MPN phase was evaluated using SEM analysis. An average thickness of 15 nm along the capillary walls was determined. While the film depth along the walls was very uniform, the corner depths were greater with the largest observed depth being 430 nm. Overall, an efficient chromatographic system was obtained with a minimum reduced plate height, hmin, of 1.2 for octane (k=0.22). Characterization of the MPN column was completed using four compound classes (alkanes, alcohols, ketones, and aromatics) that were used to form a seven-component mixture with a 2-s separation. A mixture consisting of a nerve agent simulant in a sample containing analytes that may commonly interfere with detection was also separated in only 2 s, much faster than a similar separation previously reported using a μGC system requiring 50 s. A comparison of the MPN stationary phase to phases employed in previously reported μGC systems is also made. Application of the square capillary MPN column for a high-speed separation as the second column of a comprehensive 2-D gas chromatography system (GC×GC) was also explored.
Co-reporter:Amanda E Sinha, Carlos G Fraga, Bryan J Prazen, Robert E Synovec
Journal of Chromatography A 2004 Volume 1027(1–2) pp:269-277
Publication Date(Web):20 February 2004
DOI:10.1016/j.chroma.2003.08.081
Two-dimensional comprehensive gas chromatography (GC×GC) is a powerful instrumental tool in its own right that can be used to analyze complex mixtures, generating selective data that is applicable to multivariate quantitative analysis and pattern recognition. It has been recently demonstrated that by coupling GC×GC to time-of-flight mass spectrometry (TOFMS), a highly selective technique is produced. One separation on a GC×GC/TOFMS provides retention times on two chromatographic columns and a complete mass spectrum for each component within the mixture. In this manuscript, we demonstrate how the selectivity of GC×GC/TOFMS combined with trilinear chemometric techniques such as trilinear decomposition (TLD) and parallel factor analysis (PARAFAC) results in a powerful analytical methodology. Using TLD and PARAFAC, partially resolved components in complex mixtures can be deconvoluted and identified using only one data set without requiring either signal shape assumptions or fully selective mass signals. Specifically, a region of overlapped peaks in a complex environmental sample was mathematically resolved with TLD and PARAFAC to demonstrate the utility of these techniques as applied to GC×GC/TOFMS data of a complex mixture. For this data, it was determined that PARAFAC initiated by TLD performed a better deconvolution than TLD alone. After deconvolution, mass spectral profiles were then matched to library spectra for identification. A standard addition analysis was performed on one of the deconvoluted analytes to demonstrate the utility of TLD-initiated PARAFAC for quantification without the need for accurate retention time alignment between sample and standard data sets.
Co-reporter:Amanda E. Sinha, Janiece L. Hope, Bryan J. Prazen, Erik J. Nilsson, Rhona M. Jack, Robert E. Synovec
Journal of Chromatography A 2004 Volume 1058(1–2) pp:209-215
Publication Date(Web):26 November 2004
DOI:10.1016/j.chroma.2004.08.064
The developed algorithm reported herein, referred to as “DotMap,” addresses the need to rapidly identify analyte peak locations in gas chromatography × gas chromatography–time of flight mass spectrometry (GC × GC–TOF-MS) data. The third-order structure of GC × GC–TOF-MS data is such that at each point in the GC × GC chromatogram, a complete mass spectrum is measured. DotMap utilizes this third-order structure to search for the location of a given spectrum of interest in a complete data set, or in a user selected portion of the complete data set. The algorithm returns a contour plot indicating the location of signal(s) with the most similar mass spectra to the analyte of interest. A spectrum from the region indicated is then subjected to an automated mass spectral search to give immediate feedback on the accuracy of the analysis. This algorithm was investigated with a trimethylsilyl (TMS) derivatized human infant urine sample that contained organic acid metabolites. One hundred percent of 12 selected TMS derivatized organic acid metabolites in human infant urine were located with the DotMap algorithm. A typical automated DotMap analysis takes 30 s on a 1.6 GHz PC with 1024 MB of RAM. Vanillic acid (TMS) was located by DotMap, but also exhibited overlap with other organic acids. The presence of vanillic acid (TMS) was confirmed by subjecting the appropriate GC × GC region to chemometric signal deconvolution by PARAFAC to yield pure component information suitable for subsequent quantification.
Co-reporter:Kevin J. Johnson;Bryan J. Prazen;Donald C. Young
Journal of Separation Science 2004 Volume 27(Issue 5‐6) pp:410-416
Publication Date(Web):16 FEB 2004
DOI:10.1002/jssc.200301640
Comprehensive, two-dimensional gas chromatography (GC×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×GC makes the technique attractive for the rapid, and possibly less tedious analysis of jet fuel. The analysis of complex mixtures by GC×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×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×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×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×GC chromatograms of the remaining five samples. Calibration models constructed from GC×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.
Co-reporter:Amanda E. Sinha, Bryan J. Prazen, Carlos G. Fraga, Robert E. Synovec
Journal of Chromatography A 2003 Volume 1019(1–2) pp:79-87
Publication Date(Web):26 November 2003
DOI:10.1016/j.chroma.2003.08.047
A valve-based comprehensive two-dimensional gas chromatograph coupled to a time-of-flight mass spectrometer (GC×GC/TOFMS) is demonstrated. The performance characteristics of the instrument were evaluated using a complex sample containing a mixture of fuel components, natural products, and organo-phosphorous compounds. The valve-based GC×GC, designed to function with an extended temperature of operation range, is shown to have high chromatographic resolution, high separation efficiency and low detection limits. Typical peak widths at base are nominally from 100 to 300 ms on column 2 and nominally 10 s on column 1. The injected mass and injected concentration limit of detection (LOD), defined as 3 standard deviations above the mean baseline noise, for three organo-phosphorous compounds (triethylphosphorothioate (TEPT), dimethyl methyl phosphonate (DMMP) and dimethyl phosphite (DMP)) in a complex environmental sample were from 6 to 38 pg, and 3 to 17 ng/ml, respectively. The temperature program for the environmental sample ranged from 40 to 230 °C, a temperature range capable of analyzing semi-volatile compounds. A new compact, stand-alone, valve-pulse generator device has been implemented and is also reported. The valve-based GC×GC instrument, therefore, offers a simple, rugged and less expensive alternative to thermally modulated instruments.
Co-reporter:Amanda E Sinha, Kevin J Johnson, Bryan J Prazen, Samuel V Lucas, Carlos G Fraga, Robert E Synovec
Journal of Chromatography A 2003 Volume 983(1–2) pp:195-204
Publication Date(Web):3 January 2003
DOI:10.1016/S0021-9673(02)01651-5
A high-temperature configuration for a diaphragm valve-based gas chromatography (GC×GC) instrument is demonstrated. GC×GC is a powerful instrumental tool often used to analyze complex mixtures. Previously, the temperature limitations of valve-based GC×GC instruments were set by the maximum operating temperature of the valve, typically 175 °C. Thus, valve-based GC×GC was constrained to the analysis of mainly volatile components; however, many complex mixtures contain semi-volatile components as well. A new configuration is described that extends the working temperature range of diaphragm valve-based GC×GC instruments to significantly higher temperatures, so both volatile and semi-volatile compounds can be readily separated. In the current investigation, separations at temperatures up to 250 °C are demonstrated. This new design features both chromatographic columns in the same oven with the valve interfacing the two columns mounted in the side of the oven wall so the valve is both partially inside as well as outside the oven. The diaphragm and the sample ports in the valve are located inside the oven while the temperature-restrictive portion of the valve (containing the O-rings) is outside the oven. Temperature measurements on the surface of the valve indicate that even after a sustained oven temperature of 240 °C, the portions of the valve directly involved with the sampling from the first column to the second column track the oven temperature to within 1.2% while the portions of the valve that are temperature-restrictive remain well below the maximum temperature of 175 °C. A 26-component mixture of alkanes, ketones, and alcohols whose boiling points range from 65 °C (n-hexane) to 270 °C (n-pentadecane) is used to test the new design. Peak shapes along the first column axis suggest that sample condensation or carry-over in the valve is not a problem. Chemometric data analysis is performed to demonstrate that the resulting data have a bilinear structure. After over 6 months of use and temperature conditions up to 265 °C, no deterioration of the valve or its performance has been observed.
Co-reporter:Kevin J. Johnson, Bob W. Wright, Kristin H. Jarman, Robert E. Synovec
Journal of Chromatography A 2003 Volume 996(1–2) pp:141-155
Publication Date(Web):9 May 2003
DOI:10.1016/S0021-9673(03)00616-2
A rapid retention time alignment algorithm was developed as a preprocessing utility to be used prior to chemometric analysis of large datasets of diesel fuel profiles obtained using gas chromatography (GC). Retention time variation from chromatogram-to-chromatogram has been a significant impediment against the use of chemometric techniques in the analysis of chromatographic data due to the inability of current chemometric techniques to correctly model information that shifts from variable to variable within a dataset. The alignment algorithm developed is shown to increase the efficacy of pattern recognition methods applied to diesel fuel chromatograms by retaining chemical selectivity while reducing chromatogram-to-chromatogram retention time variations and to do so on a time scale that makes analysis of large sets of chromatographic data practical. Two sets of diesel fuel gas chromatograms were studied using the novel alignment algorithm followed by principal component analysis (PCA). In the first study, retention times for corresponding chromatographic peaks in 60 chromatograms varied by as much as 300 ms between chromatograms before alignment. In the second study of 42 chromatograms, the retention time shifting exhibited was on the order of 10 s between corresponding chromatographic peaks, and required a coarse retention time correction prior to alignment with the algorithm. In both cases, an increase in retention time precision afforded by the algorithm was clearly visible in plots of overlaid chromatograms before and then after applying the retention time alignment algorithm. Using the alignment algorithm, the standard deviation for corresponding peak retention times following alignment was 17 ms throughout a given chromatogram, corresponding to a relative standard deviation of 0.003% at an average retention time of 8 min. This level of retention time precision is a 5-fold improvement over the retention time precision initially provided by a state-of-the-art GC instrument equipped with electronic pressure control and was critical to the performance of the chemometric analysis. This increase in retention time precision does not come at the expense of chemical selectivity, since the PCA results suggest that essentially all of the chemical selectivity is preserved. Cluster resolution between dissimilar groups of diesel fuel chromatograms in a two-dimensional scores space generated with PCA is shown to substantially increase after alignment. The alignment method is robust against missing or extra peaks relative to a target chromatogram used in the alignment, and operates at high speed, requiring roughly 1 s of computation time per GC chromatogram.
Co-reporter:Sumalee Tanikkul, Jaroon Jakmunee, Mongkon Rayanakorn, Kate Grudpan, Brian J Marquardt, Gwen M Gross, Bryan J Prazen, Lloyd W Burgess, Gary D Christian, Robert E Synovec
Talanta 2003 Volume 59(Issue 4) pp:809-816
Publication Date(Web):10 March 2003
DOI:10.1016/S0039-9140(02)00623-9
A novel Raman sensor using a liquid-core optical waveguide is reported, implementing a Teflon-AF 2400 tube filled with water. An aqueous analyte mixture of benzene, toluene and p-xylene was introduced using a 1000 μl sample loop to the liquid-core waveguide (LCW) sensor and the analytes were preconcentrated on the inside surface of the waveguide tubing. The analytes were then eluted from the waveguide using an acetonitrile–water solvent mixture injected via a 30 μl eluting solvent loop. The preconcentration factor was experimentally determined to be 14-fold, in reasonable agreement with the theoretical preconcentration factor of 33 based upon the sample volume to elution volume ratio. Raman spectra of benzene, toluene and p-xylene were obtained during elution. It was found that analytically useful Raman signals for benzene, toluene and p-xylene were obtained at 992, 1004 and 1206 cm−1, respectively. The relative standard deviation of the method was 3% for three replicate measurements. The limit of detection (LOD) was determined to be 730 ppb (parts per billion by volume) for benzene, exceptional for a system that does not resort to surface enhancement or resonance Raman approaches. The Raman spectra of these test analytes were evaluated for qualitative and quantitative analysis utility.
Co-reporter:Narong Lenghor, Kate Grudpan, Jaroon Jakmunee, Bethany A Staggemeier, Wes W.C Quigley, Bryan J Prazen, Gary D Christian, Jaromir Ruzicka, Robert E Synovec
Talanta 2003 Volume 59(Issue 6) pp:1153-1163
Publication Date(Web):1 May 2003
DOI:10.1016/S0039-9140(03)00022-5
A sequential injection analysis (SIA) system is coupled with dynamic surface tension detection (DSTD) for the purpose of studying the interfacial properties of surface-active samples. DSTD is a novel analyzer based upon a growing drop method, utilizing a pressure sensor measurement of drop pressure. The pressure signal depends on the surface tension properties of sample solution drops that grow and detach at the end of a capillary tip. In this work, SIA was used for creating a reagent concentration gradient, and for blending the reagent gradient with a steady-state sample. The sample, consisting of either sodium dodecyl sulfate (SDS) or poly(ethylene glycol) at 1470 g mol−1 (PEG 1470), elutes with a steady-state concentration at the center of the sample plug. Reagents such as Brij®35, tetrabutylammonium (TBA) hydroxide and β-cyclodextrin were introduced as a concentration gradient that begins after the sample plug has reached the steady-state concentration. By blending the reagent concentration gradient with the sample plug using SIA/DSTD, the kinetic surface pressure signal of samples mixed with various reagent concentrations is observed and evaluated in a high throughput fashion. It was found that the SIA/DSTD method consumes lesser reagent and required significantly less analysis time than traditional FIA/DSTD. Four unique chemical systems were studied with regard to how surface activity is influenced, as observed through the surface tension signal: surface activity addition, surface activity reduction due to competition, surface activity enhancement due to ion-pair formation, and surface activity reduction due to bulk phase binding chemistry.
Co-reporter:Bryan J. Prazen;Kevin J. Johnson;Roy K. Olund
Journal of Separation Science 2002 Volume 25(Issue 5‐6) pp:297-303
Publication Date(Web):11 APR 2002
DOI:10.1002/1615-9314(20020401)25:5/6<297::AID-JSSC297>3.0.CO;2-I
A diaphragm valve-based comprehensive two-dimensional gas chromatography (GC×GC) instrument with the two columns under independent temperature control is demonstrated. A fifteen-component mixture of alkanes, alkyl aromatics, ketones, and alcohols was separated using this system in only 45 s. Independent temperature control of the two columns allows for high-speed analysis of complex samples while retaining the bilinear data structure that is necessary to apply many chemometric peak-resolving methods. An important part of high-speed GC×GC is sharp injections onto the second column. In this work, 10-ms peak widths on the second column are demonstrated. A peak capacity per time of 240 peaks/min was readily achieved. This work is aimed at providing a high-speed GC system for the quantitative and qualitative analysis of complex process streams, such as natural products.
Co-reporter:Colin D Costin, Robert E Synovec
Talanta 2002 Volume 58(Issue 3) pp:551-560
Publication Date(Web):12 September 2002
DOI:10.1016/S0039-9140(02)00321-1
A detection scheme that probes the refractive index gradient (RIG) between adjacent laminar flows in microfluidic devices has been developed and evaluated. The behavior of low Reynolds number flows has been well documented and shows that molecular transport (mixing) between adjacent laminar flows occurs by molecular diffusion between the flow boundaries. A diode laser has been used to probe the transverse concentration gradient at a selected position along a microchannel. The concentration gradient is affected by the transverse diffusion from a flow with analyte into a flow initially without analyte. To optimize sensitivity, the RIG is probed at a position in which molecular diffusion across the boundary of the two flows has been minimal, i.e. just after the flow initially without analyte merges with the flow initially containing the analyte at a given concentration. The RIG formed causes the laser beam, impinging orthogonal to the RIG through the microchannel, to be deflected. The angle of deflection is then monitored on a position sensitive detector (PSD). Currently, this detection scheme is demonstrated to provide quantitative detection of sucrose, as a test analyte, with a concentration limit of detection (LOD) of 96 ppm (w/v) or 280 μM, corresponding to 1.3×10−5 ΔRI units using 3σ baseline noise. A dynamic range of 96 ppm to 50% sucrose is obtained. This detection method provides universal detection selectivity for microfluidic analysis systems that are becoming increasingly useful in monitoring chemical systems, particularly for the polymer, pharmaceutical and life sciences fields. For a larger molecular weight analyte with a smaller diffusion coefficient, lower concentration and RI LODs were achieved since detection sensitivity is a function of analyte diffusion. For example, for the polymer poly (ethylene glycol) with a molar mass of 11 840 g mol−1, the LOD was experimentally determined to be 56 ppm (4.7 μM), equivalent to a RI LOD of 4.5×10−6 ΔRI (3σ). The detection limit for proteins was also found to be favorable. For example, with the current configuration, ribonuclease A (RNAse) had a LOD of 46 ppm (3.4 μM), and bovine serum albumin (BSA) had a LOD of 54 ppm (780 nM).
Co-reporter:Wes W.C. Quigley, Abdul Nabi, Bryan J. Prazen, Narong Lenghor, Kate Grudpan, Robert E. Synovec
Talanta 2001 Volume 55(Issue 3) pp:551-560
Publication Date(Web):13 September 2001
DOI:10.1016/S0039-9140(01)00458-1
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 (∼4 μl) from a spherical shape is readily observed and deviates more significantly by ∼6 μl 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 μl (two second drops at 60 μl/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.
Co-reporter:Keith E Miller, Robert E Synovec
Talanta 2000 Volume 51(Issue 5) pp:921-933
Publication Date(Web):28 April 2000
DOI:10.1016/S0039-9140(99)00358-6
The use of drops in chemical analysis methodology and instrumentation has a deeply rooted past in the area of electrochemistry through the evolution of the dropping mercury electrode (DME). This history has also been deeply rooted in the field of surface science due to the inextricable connection between surface tension forces and drop formation. While the use of the DME is well established, the evolution of drop-based analytical measurements using aqueous and/or organic drops is a rapidly emerging and diverse field, encompassing several interdisciplinary areas of science: surface science and interfacial surface tension phenomena, spectroscopic detection, analytical instrumentation hyphenation, liquid membrane separation, reagent chemistry, electrochemistry, and so on. This review of 112 references covers various aspects of drop-based analytical measurements involving aqueous and/or organic drops. The review is divided into four sections, although the classification of a particular reference into a given section can sometimes be argued. The first section considers the use of drops as a detector component. The second section deals with fundamental studies that probe drop-related chemical and physical phenomena that are relevant to current and future developments in analytical chemistry. The next section covers recent advances in the area of microfluidic sample handling and instrumentation hyphenation. The final section reports upon emerging technologies aimed toward drop-based chemical analyzers that incorporate a number of steps in a chemical analysis: microextraction, preconcentration, reagent chemistry, microfluidic handling, and detection.
Co-reporter:Paul G Vahey, Sang Hyun Park, Brian J Marquardt, Younan Xia, Lloyd W Burgess, Robert E Synovec
Talanta 2000 Volume 51(Issue 6) pp:1205-1212
Publication Date(Web):5 May 2000
DOI:10.1016/S0039-9140(00)00311-8
A rapid and low-cost means of developing a working prototype for a positive-displacement driven open tubular liquid chromatography (OTLC) analyzer is demonstrated. A novel flow programming and injection strategy was developed and implemented using soft lithography, and evaluated in terms of chromatographic band broadening and efficiency. A separation of two food dyes served as the model sample system. Sample and mobile phase flowed continuously by positive displacement through the OTLC analyzer. Rectangular channels, of dimensions 10 μm deep by 100 μm wide, were micro-fabricated in poly-dimethylsiloxane (PDMS), with the separation portion 6.6 cm long. Using a novel flow programming method, in contrast to electroosmotic flow, sample injection volumes from 0.5 to 10 nl were made in real-time. Band broadening increased substantially for injection volumes over 1 nl. Although underivatized PDMS proved to be a sub-optimal stationary phase, plate heights, H, of 12 μm were experimentally achieved for an unretained analyte with the rectangular channel resulting in a reduced plate height, h, of 1.2. Chromatographic efficiency of the unretained analyte followed the model of an OTLC system limited by mass-transfer in the mobile phase. Flow rates from 6 nl min−1 up to 200 nl min−1 were tested, and van Deemter plots confirmed plate heights were optimum at 6 nl min−1 over the tested flow rate range. Thus, the best separation efficiency, N of 5500 for the 6.6 cm length separation channel, was achieved at the minimum flow rate through the column of 6 nl min−1, or 3 ml year−1. This analyzer is a low-cost sampling and chemical analysis tool that is intended to complement micro-fabricated electrophoretic and related separation devices.
Co-reporter:Keith E. Miller, Kristen J. Skogerboe, Robert E. Synovec
Talanta 1999 Volume 50(Issue 5) pp:1045-1056
Publication Date(Web):December 1999
DOI:10.1016/S0039-9140(99)00210-6
First, a novel technique for calibration of a dynamic surface tension detector (DSTD) is described. The DSTD measures the differential pressure as a function of time across the liquid–air interface of growing drops that repeatedly form and detach at the end of a capillary tip. The calibration technique utilizes the ratio of pressure signals acquired from the drop growth of two separate solutions, i.e. a standard solution and a corresponding mobile phase, such as water, both of which have a known surface tension. Once calibrated, the dynamic surface tension of an analyte is obtained from the ratio of the pressure signals from the analyte solution to that of the mobile phase solution. Thus, this calibration technique eliminates the need to optically image the radius of the expanding drop of liquid. Accurate dynamic surface tension determinations were achieved for aqueous sodium dodecyl sulfate (SDS) solutions over a concentration range of 0.5–5.4 mM. The measured surface tensions for these SDS solutions range from 70.3 to 46.8 dyne/cm and were in excellent agreement with the literature. A precision of 0.2 dyne/cm (1 S.D.) was routinely obtained. Second, the DSTD with this calibration technique was combined with flow injection analysis (FIA) for the study of model protein solutions and polymer solutions. The kinetic surface tension behavior of aqueous bovine serum albumin (BSA) solutions as a function of concentration and flow rate is presented. Evaluation of the dynamic surface tension data illustrates that a protein such as BSA initially exhibits kinetically-hindered surface tension lowering, i.e. a time dependence, as BSA interacts with the liquid–air interface of an expanding drop. FIA/DSTD is then shown to be an effective tool for the rapid study of kinetically-hindered surfactant mixtures. It was found that mixtures of SDS and the polymeric surfactant Brij®-35 (lauryl polyoxyethylene ether with an average molecular weight of 1200 g/mol) result in essentially an additive lowering of the surface tension. Mixtures of polyethylene glycol (PEG), with an average molecular weight of 1470 g/mol, and Brij®-35, however, result in a competitive (non-additive) surface tension with the Brij®-35 dominating the response.
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