Publications

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Recent news reports coming from Asia and the UK have highlighted the emerging threats of Non-Traditional Agents (NTAs) to national security. The UK incident underscores how NTAs may linger in the environment and at trace. Building on Sandia's extensive analytical chemistry work in this field, a polysilphenylene analog of Sandia's proprietary DKAP polymer coatings was synthesized and evaluated for high temperature operation. Initial test results are inconclusive as to the improved thermal stability of the new polymer with TGA/DSC results indicating a lower glass transition go temperature for the new "Hot DKAP" material and a similar to slightly lower start to mass loss for "Hot DKAP", but slower degradation rate in clean dry air. Additional testing with a TGA-MS system to identify what the fragments lost as a function of temperature is still needed to fully characterize the materials thermal properties. In addition, the material still needs to be evaluated for thermodynamic properties for analytes of interest using either GC or SPC coated devices. ACKNOWLEDGEMENTS The authors would like to gratefully acknowledge the contributions and assistance of Eric Coker and Lindsey Hughes.

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A small, consumable-free, low-power, ultra-high-speed comprehensive GC×GC system consisting of microfabricated columns, nanoelectromechanical system (NEMS) cantilever resonators for detection, and a valve-based stop-flow modulator is demonstrated. The separation of a highly polar 29-component mixture covering a boiling point range of 46 to 253 °C on a pair of microfabricated columns using a Staiger valve manifold in less than 7 seconds, and just over 4 seconds after the ensemble holdup time is demonstrated with a downstream FID. The analysis time of the second dimension was 160 ms, and peak widths in the second dimension range from 10-60 ms. A peak capacity of just over 300 was calculated for a separation of just over 6 s. Data from a continuous operation testing over 40 days and 20000 runs of the GC×GC columns with the NEMS resonators using a 4-component test set is presented. The GC×GC-NEMS resonator system generated second-dimension peak widths as narrow as 8 ms with no discernable peak distortion due to under-sampling from the detector.

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We describe for the first time hydrogen bonded acid (HBA) polymer, poly[methyl[3-(2-hydroxyl, 4,6-bistrifluoromethyl)- phenyl]propylsiloxane], (DKAP), as stationary phase for gas chromatography (μGC) of organophosphate (OP), chemical warfare agent (CWA) surrogates, dimethylmethylphosphonate (DMMP), diisopropylmethylphosphonate (DIMP), diethylmethylphosphonate (DEMP), and trimethylphosphate (TMP), with high selectivity. Absorption of OPs to DKAP was one-to-several orders of magnitude higher relative to commercial polar, mid-polar, and nonpolar stationary phases. We also present for the first-time thermodynamic studies on the absorption of OP vapors and quantitative binding energy data for interactions with various stationary phases. These data help to identify the best pair of hetero-polar columns for a two-dimensional GC system, employing a nonpolar stationary phase as GC1 and DKAP as the GC2 stationary phase, for selective and rapid field detection of CWAs.

Gas Chromatography (GC) is routinely used in the laboratory to temporally separate chemical mixtures into their constituent components for improved chemical identification. This paper will provide a overview of more than twenty years of development of one-dimensional field-portable micro GC systems, highlighting key experimental results that illustrate how a reduction in false alarm rate (FAR) is achieved in real-world environments. Significantly, we will also present recent results on a micro two-dimensional GC (micro GCxGC) technology. This ultra-small system consists of microfabricated columns, NanoElectroMechanical System (NEMS) cantilever resonators for detection, and a valve-based stop-flow modulator. The separation of a 29-component polar mixture in less than 7 seconds is demonstrated along with peak widths in the second dimension ranging from 10-60 ms. For this system, a peak capacity of just over 300 was calculated for separation in about 6 s. This work has important implications for field detection, to drastically reduce FAR and significantly improve chemical selectivity and identification. This separation performance was demonstrated with the NEMS resonator and bench scale FID. But other detectors, suitably fast and sensitive can work as well. Recent research has shown that the identification power of GCxGC-FID can match that of GC-MS. This result indicates a path to improved size, weight, power, and performance in micro GCxGC systems outfitted with relatively non-specific, lightweight detectors. We will briefly discuss the performance of possible options, such as the pulsed discharge helium ionization detector (PDHID) and miniature correlation ion mobility spectrometer (mini-CIMS).

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In gas chromatography, a chemical sample separates into its constituent components as it travels along a long thin column. As the component chemicals exit the column they are detected and identified, allowing the chemical makeup of the sample to be determined. For correct identification of the component chemicals, the distribution of the concentration of each chemical along the length of the column must be nearly symmetric. The prediction and control of asymmetries in gas chromatography has been an active research area since the advent of the technique. In this paper, we develop from first principles a general model for isothermal linear chromatography. We use this model to develop closed-form expressions for terms related to the first, second, and third moments of the distribution of the concentration, which determines the velocity, diffusion rate, and asymmetry of the distribution. We show that for all practical experimental situations, only fronting peaks are predicted by this model, suggesting that a nonlinear chromatography model is required to predict tailing peaks. For situations where asymmetries arise, we analyze the rate at which the concentration distribution returns to a normal distribution. Numerical examples are also provided.