Vapor Pressure of Hexamethylene Triperoxide Diamine (HMTD) Estimated Using Secondary Electrospray Ionization Mass Spectrometry.

A rapid method for vapor pressure measurement was developed and used to derive the vapor pressure curve of the thermally labile peroxide-based explosive hexamethylene triperoxide diamine (HMTD) over the temperature range from 28 to 80 °C. This method uses a controlled flow of vapor from a solid-phase HMTD source that is presented to an ambient-pressure-ionization mass spectrometer equipped with a secondary-electrospray-ionization (SESI) source. The subpart-per-trillion sensitivity of this system enables direct detection of HMTD vapor through an intact [M + H](+) ion in real time at temperatures near 20 °C. By calibrating this method using vapor sources of cocaine and heroin, which have known pressure-temperature (P-T) curves, the temperature dependence of HMTD vapor was determined, and a Clausius-Clapeyron plot of ln[P (Pa)] vs 1/[T (K)] yielded a straight line with the expression ln[P (Pa)] = {(-11091 ± 356) × 1/[T (K)]} + 25 ± 1 (error limits are the standard error of the regression analysis). From this equation, the sublimation enthalpy of HMTD was estimated to be 92 ± 3 kJ/mol, which compares well with the theoretical estimate of 95 kJ/mol, and the vapor pressure at 20 °C was estimated to be ∼60 parts per trillion by volume, which is within a factor of 2 of previous theoretical estimates. Thus, this method provides not only the first direct experimental determination of HMTD vapor pressure but also a rapid, near-real-time capability to quantitatively measure low-vapor-pressure compounds, which will be useful for aiding in the development of training aids for bomb-sniffing canines.

Fate dynamics of environmentally exposed explosive traces.

The chemical and physical fates of trace amounts (<50 µg) of explosives containing 2,4,6-trinitrotoluene (TNT), hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), and pentaerythritol tetranitrate (PETN) were determined for the purpose of informing the capabilities of tactical trace explosive detection systems. From these measurements, it was found that the mass decreases and the chemical composition changes on a time scale of hours, with the loss mechanism due to a combination of sublimation and photodegradation. The rates for these processes were dependent on the explosive composition, as well as on both the ambient temperature and the size distribution of the explosive particulates. From these results, a persistence model was developed and applied to model the time dependence of both the mass and areal coverage of the fingerprints, resulting in a predictive capability for determining fingerprint fate. Chemical analysis confirmed that sublimation rates for TNT were depressed by UV (330-400 nm) exposure due to photochemically driven increases in the molecular weight, whereas the opposite was observed for RDX. No changes were observed for PETN upon exposure to UV radiation, and this was attributed to its low UV absorbance.

Artificial noses.

The mammalian olfactory system is able to detect many more odorants than the number of receptors it has by utilizing cross-reactive odorant receptors that generate unique response patterns for each odorant. Mimicking the mammalian system, artificial noses combine cross-reactive sensor arrays with pattern recognition algorithms to create robust odor-discrimination systems. The first artificial nose reported in 1982 utilized a tin-oxide sensor array. Since then, however, a wide range of sensor technologies have been developed and commercialized. This review highlights the most commonly employed sensor types in artificial noses: electrical, gravimetric, and optical sensors. The applications of nose systems are also reviewed, covering areas such as food and beverage quality control, chemical warfare agent detection, and medical diagnostics. A brief discussion of future trends for the technology is also provided.

Detection and classification of ignitable liquid residues using a fluorescence-based vapor-sensitive microsphere array.

This paper describes the application of microsphere vapor sensing arrays to the detection of ignitable liquid (IL) vapors as both pure vapors and as residues (ILRs) on simulated fire debris samples. The temporal fluorescence response profile of the microsphere array generated a reproducible pattern unique to each analyte that could be used to classify subsequent sensor responses. This system, together with a support vector machine pattern recognition algorithm, was used to address several different IL and ILR classification scenarios. High classification accuracy (98%) was maintained over more than 200 vapor responses and the array was able to identify ILs when presented to the pattern classification algorithm within a dataset containing 11 other volatile compounds. Both burned and unburned IL treated samples were classified correctly greater than 97% of the time. These results indicate that microsphere vapor sensing arrays may be useful for the rapid identification of ILs and ILRs.

Design, implementation, and field testing of a portable fluorescence-based vapor sensor.

The design and implementation of a portable fluorescence-based vapor sensing system are described. The system incorporates previously developed microsensor array technology into a compact, low-power device capable of collecting and delivering ambient vapor samples to the array while monitoring and recording the fluorescent responses of the sensors. The sensors respond differentially when exposed to a sample vapor and, when processed using a support vector machine (SVM) pattern recognition algorithm, are shown to discriminate between three classes of petroleum distillates. The system was characterized using sample vapors prepared under several different conditions in three sensing scenarios. The first scenario demonstrates the basic operational capability of the device in the field by presenting high concentration vapors to the array. The second scenario introduces the potential for a greater degree of variability in both sample vapor concentration and composition in an effort to emulate real-world sensing conditions. The third scenario uses an on-board trained pattern recognition algorithm to identify unknown vapors as their responses are collected. The device demonstrated high classification accuracy throughout the field tests and is capable of improving its classification accuracy when challenged with samples presented under variable ambient conditions by enhancing the signal-to-noise ratio of the array response.

Temporally resolved fluorescence spectroscopy of a microarray-based vapor sensing system.

This paper describes a method to measure the complete fluorescence spectrum from numerous fluorescent microspheres in a microarray simultaneously during exposure to a vapor. The technique, called spectrally resolved sensor imaging (SRSI), positions a transmission grating directly in front of the microscope objective on a standard epi-fluorescence microscope. This modification produces a hybrid image on the CCD camera that contains a conventional fluorescence image in the zero-order diffracted light and a fluorescence spectral image in the first-order diffracted light. Three types of surface-functionalized silica microspheres were coated with a solvatochromic dye. The surface functionality on the microspheres influences the maximum emission wavelength of the dye and generates a fluorescence spectral signature that is used to identify each sensor type. These sensors were randomly distributed into a photolithographically fabricated microarray platform, and the spectral signature of each individual sensor was measured. The time resolution of spectral acquisition is short enough to capture dynamic changes in the fluorescence emission as a vapor is presented to the array. The ability to measure the entire fluorescence spectrum from each sensor simultaneously during a vapor exposure increases the dimensionality of the response data and significantly improves the classification accuracy of the system.