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.

Elemental source attribution signatures for calcium ammonium nitrate (CAN) fertilizers used in homemade explosives.

Calcium ammonium nitrate (CAN) is a widely available fertilizer composed of ammonium nitrate (AN) mixed with some form of calcium carbonate such as limestone or dolomite. CAN is also frequently used to make homemade explosives. The potential of using elemental profiling and chemometrics to match both pristine and reprocessed CAN fertilizers to their factories of origin for use in future forensic investigations was examined. Inductively coupled plasma-mass spectrometry (ICP-MS) was used to determine the concentrations of 64 elements in 125 samples from 11 CAN stocks from 6 different CAN factories. Using Fisher ratio and degree-of-class-separation, the elements Na, V, Mn, Cu, Ga, Sr, Ba and U were selected for classification of the CAN samples into 5 factory groups; one group was two factories from the same fertilizer company. Partial least squares discriminant analysis (PLSDA) was used to develop a classification model which was tested on a separate set of samples. The test set included samples that were analyzed at a different time period and samples from factory stocks that were not part of the training set. For pristine CAN samples, i.e., unadulterated prills, 73% of the test samples were matched to their correct factory group with the remaining 27% undetermined using strict classification. The same PLSDA model was used to correctly match all CAN samples that were reprocessed by mixing with powdered sugar. For CAN samples that were reprocessed by mixing with aluminum or by extraction of AN with tap or bottled water, correct classification was observed for one factory group, but source matching was confounded with adulterant interference for two other factories. The elemental signatures of the water-insoluble (calcium carbonate) portions of CAN provided a greater degree of discrimination between factories than the water-soluble portions of CAN. In summary, this work illustrates the strong potential for matching unadulterated CAN fertilizer samples to their manufacturing facility using elemental profiling and chemometrics. The effectiveness of this method for source determination of reprocessed CAN is dependent on how much an adulterant alters the recovered elemental profile of CAN.

Organic Chemical Attribution Signatures for the Sourcing of a Mustard Agent and Its Starting Materials.

Chemical attribution signatures (CAS) are being investigated for the sourcing of chemical warfare (CW) agents and their starting materials that may be implicated in chemical attacks or CW proliferation. The work reported here demonstrates for the first time trace impurities from the synthesis of tris(2-chloroethyl)amine (HN3) that point to the reagent and the specific reagent stocks used in the synthesis of this CW agent. Thirty batches of HN3 were synthesized using different combinations of commercial stocks of triethanolamine (TEA), thionyl chloride, chloroform, and acetone. The HN3 batches and reagent stocks were then analyzed for impurities by gas chromatography/mass spectrometry. All the reagent stocks had impurity profiles that differentiated them from one another. This was demonstrated by building classification models with partial least-squares discriminant analysis (PLSDA) and obtaining average stock classification errors of 2.4, 2.8, 2.8, and 11% by cross-validation for chloroform (7 stocks), thionyl chloride (3 stocks), acetone (7 stocks), and TEA (3 stocks), respectively, and 0% for a validation set of chloroform samples. In addition, some reagent impurities indicative of reagent type were found in the HN3 batches that were originally present in the reagent stocks and presumably not altered during synthesis. More intriguing, impurities in HN3 batches that were apparently produced by side reactions of impurities unique to specific TEA and chloroform stocks, and thus indicative of their use, were observed.

Automated methods for multiplexed pathogen detection.

Detection of pathogenic microorganisms in environmental samples is a difficult process. Concentration of the organisms of interest also co-concentrates inhibitors of many end-point detection methods, notably, nucleic acid methods. In addition, sensitive, highly multiplexed pathogen detection continues to be problematic. The primary function of the BEADS (Biodetection Enabling Analyte Delivery System) platform is the automated concentration and purification of target analytes from interfering substances, often present in these samples, via a renewable surface column. In one version of BEADS, automated immunomagnetic separation (IMS) is used to separate cells from their samples. Captured cells are transferred to a flow-through thermal cycler where PCR, using labeled primers, is performed. PCR products are then detected by hybridization to a DNA suspension array. In another version of BEADS, cell lysis is performed, and community RNA is purified and directly labeled. Multiplexed detection is accomplished by direct hybridization of the RNA to a planar microarray. The integrated IMS/PCR version of BEADS can successfully purify and amplify 10 E. coli O157:H7 cells from river water samples. Multiplexed PCR assays for the simultaneous detection of E. coli O157:H7, Salmonella, and Shigella on bead suspension arrays was demonstrated for the detection of as few as 100 cells for each organism. Results for the RNA version of BEADS are also showing promising results. Automation yields highly purified RNA, suitable for multiplexed detection on microarrays, with microarray detection specificity equivalent to PCR. Both versions of the BEADS platform show great promise for automated pathogen detection from environmental samples. Highly multiplexed pathogen detection using PCR continues to be problematic, but may be required for trace detection in large volume samples. The RNA approach solves the issues of highly multiplexed PCR and provides "live vs. dead" capabilities. However, sensitivity of the method will need to be improved for RNA analysis to replace PCR.

Automated portable analyzer for lead(II) based on sequential flow injection and nanostructured electrochemical sensors.

A fully automated portable analyzer for toxic metal ion detection based on a combination of a nanostructured electrochemical sensor and a sequential flow injection system has been developed in this work. The sensor was fabricated from a carbon paste electrode modified with acetamide phosphonic acid self-assembled monolayer on mesoporous silica (Ac-Phos SAMMS) which was embedded in a very small wall-jet (flow-onto) electrochemical cell. The electrode is solid-state and mercury-free. Samples and reagents were injected into the system and flowed through the electrochemical cell by a user programmable sequential flow technique which required minimal volume of samples and reagents and allowed the automation of the analyzer operation. The portable analyzer was evaluated for lead (Pb) detection due to the excellent binding affinity between Pb and the functional groups of Ac-Phos SAMMS as well as the great concern for Pb toxicity. Linear calibration curve was obtained in a low concentration range (1-25ppb of Pb(II)). The reproducibility was excellent; the percent relative standard deviation was 2.5 for seven consecutive measurements of 10ppb of Pb(II) solution. Excess concentrations of Ca, Ni, Co, Zn, and Mn ions in the solutions did not interfere with detection of Pb, due to the specificity and the large number of the functional groups on the electrode surface. The electrode was reliable for at least 90 measurements over 5 days. This work is an important milestone in the development of the next-generation metal ion analyzers that are portable, fully automated, and remotely controllable.