Physicochemical Gas-Solid Sorption Properties of Geologic Materials Using Inverse Gas Chromatography.

The goal of this study was to determine the physicochemical properties of a variety of geologic materials using inverse gas chromatography (IGC) by varying probe gas selection, temperature, carrier gas flow rate, and humidity. This is accomplished by measuring the level of interaction between the materials of interest and known probe gases. Identifying a material's physicochemical characteristics can help provide a better understanding of the transport of gaseous compounds in different geologic materials or between different geological layers under various conditions. Our research focused on measuring the enthalpy (heat) of adsorption, Henry's constant, and diffusion coefficients of a suite of geologic materials, including two soil types (sandy clay-loam and loam), quartz sand, salt, and bentonite clay, with various particle sizes. The reproducibility of IGC measurements for geologic materials, which are inherently heterogeneous, was also assessed in comparison to the reproducibility for more homogeneous synthetic materials. This involved determining the variability of physicochemical measurements obtained from different IGC approaches, instruments, and researchers. For the investigated IGC-determined parameters, the need for standardization became apparent, including the need for application-relevant reference materials. The inherent physical and chemical heterogeneities of soil and many geologic materials can make the prediction of sorption properties difficult. Characterizing the properties of individual organic and inorganic components can help elucidate the primary factors influencing sorption interactions in more complex mixtures. This research examined the capabilities and potential challenges of characterizing the gas sorption properties of geologic materials using IGC.

Correlation of rocket propulsion fuel properties with chemical composition using comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry followed by partial least squares regression analysis.

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.

Impurity profiling of a chemical weapon precursor for possible forensic signatures by comprehensive two-dimensional gas chromatography/mass spectrometry and chemometrics.

In this report we present the feasibility of using analytical and chemometric methodologies to reveal and exploit the chemical impurity profiles from commercial dimethyl methylphosphonate (DMMP) samples to illustrate the type of forensic information that may be obtained from chemical-attack evidence. Using DMMP as a model compound of a toxicant that may be used in a chemical attack, we used comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (GC x GC/TOF-MS) to detect and identify trace organic impurities in six samples of commercially acquired DMMP. The GC x GC/TOF-MS data was analyzed to produce impurity profiles for all six DMMP samples using 29 analyte impurities. The use of PARAFAC for the mathematical resolution of overlapped GC x GC peaks ensured clean spectra for the identification of many of the detected analytes by spectral library matching. The use of statistical pairwise comparison revealed that there were trace impurities that were quantitatively similar and different among five of the six DMMP samples. Two of the DMMP samples were revealed to have identical impurity profiles by this approach. The use of nonnegative matrix factorization indicated that there were five distinct DMMP sample types as illustrated by the clustering of the multiple DMMP analyses into five distinct clusters in the scores plots. The two indistinguishable DMMP samples were confirmed by their chemical supplier to be from the same bulk source. Sample information from the other chemical suppliers supported the idea that the other four DMMP samples were likely from different bulk sources. These results demonstrate that the matching of synthesized products from the same source is possible using impurity profiling. In addition, the identified impurities common to all six DMMP samples provide strong evidence that basic route information can be obtained from impurity profiles. Finally, impurities that may be unique to the sole bulk manufacturer of DMMP were found in some of the DMMP samples.

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

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

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

Two-dimensional comprehensive gas chromatography (GC x 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 x GC to time-of-flight mass spectrometry (TOFMS), a highly selective technique is produced. One separation on a GC x GC/TOFMS provides retention times on two chromatographic columns and a complete mass spectrum for each component within the mixture. In this manuscript, we demonstrate how the selectivity of GC x 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 x 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.

Chemometric approach for the resolution and quantification of unresolved peaks in gas chromatography--selected-ion mass spectrometry data.

A semiautomated and integrated chemometric approach is presented for the resolution and quantification of unresolved target-analyte signals in gas chromatography-selected-ion monitoring (GC-SIM) data collected using scanning mass spectrometers. The chemometric approach utilizes an unskewing algorithm and two multivariate chemometric methods known as rank alignment and the generalized rank annihilation method (GRAM). The unskewing algorithm corrects the retention-time differences within a single GC-SIM data matrix caused by using a scanning mass spectrometer. Rank alignment objectively corrects the run-to-run retention-time difference between a sample GC-SIM data matrix and a standard addition GC-SIM data matrix. GRAM analysis uses the sample and standard addition data matrices to mathematically resolve and quantify the target-analyte signal(s). The resolution and quantification of severely unresolved target-analyte signals are demonstrated using GC-SIM data obtained from conventional heart-cut two-dimensional gas chromatography with mass spectrometric detection. In addition, the GC-SIM data is used to demonstrate the result of chemometric analysis when the absence of a target-analyte signal is obscured by interference. Chemometric analysis is shown to unambiguously detect an analyte based on its resolved mass chromatograms in situations where the traditional approach of measuring peak height fails to positively detect it. The predicted analyte concentrations are within 8% of the reference concentrations.

Valve-based comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometric detection: instrumentation and figures-of-merit.

A valve-based comprehensive two-dimensional gas chromatograph coupled to a time-of-flight mass spectrometer (GC x 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 x 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 degrees 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 x GC instrument, therefore, offers a simple, rugged and less expensive alternative to thermally modulated instruments.

Comprehensive two-dimensional gas chromatography of volatile and semi-volatile components using a diaphragm valve-based instrument.

A high-temperature configuration for a diaphragm valve-based gas chromatography (GCXGC) instrument is demonstrated. GCxGC is a powerful instrumental tool often used to analyze complex mixtures. Previously, the temperature limitations of valve-based GCxGC instruments were set by the maximum operating temperature of the valve, typically 175 degrees C. Thus, valve-based GCxGC 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 GCxGC 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 degrees 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 degrees 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 degrees C. A 26-component mixture of alkanes, ketones, and alcohols whose boiling points range from 65 degrees C (n-hexane) to 270 degrees 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 degrees C, no deterioration of the valve or its performance has been observed.