Sonic spray vaporization of liquid samples for introduction to hand-held ion mobility spectrometry vapor analyzers.

On-site identification of organic compounds in the presence of interfering materials using a field-portable attenuated total reflection Fourier transform infrared (ATR FT-IR) spectrometer is presented. Identification is based on an algorithm that compares the analyte's infrared absorption spectrum with the reference spectra. The comparison is performed at several predetermined frequencies, and a similarity value (distance) between the measured and the reference spectra is calculated either at each frequency individually, or, alternatively, the average distance for all frequencies is calculated. The examined frequencies are selected to give the best contrast between the target materials of interest. In this study, the algorithm was optimized to identify three common chemical warfare agents (CWAs): O-ethyl S-[2-(diisopropylamino)ethyl] methylphosphonothioic acid (VX), sarin (GB), and sulfur mustard (bis(2-chloroethyl) sulfide) (HD), in the presence of field-related interfering materials (fuels, water, and dust). Receiver operating characteristics analysis was performed in order to determine the probabilities for detection (PD) and for false alerts (PF). Challenging the algorithm with a set of data that contains mixtures of CWAs and interfering materials resulted in PD of 90% and PF of 0%, 0%, and 1% for VX, GB, and HD, respectively, using the average distance approach, which was found to be much more effective than analyzing each frequency individually. This finding was validated for all possible combinations of 2–7 peaks per material. It is suggested that this algorithm provides a reliable mean for the identification of a predetermined set of target analytes and interfering materials.

Chemical analysis of hazardous surface contaminations, such as hazardous substances, explosives or illicit drugs, is an essential task in security, environmental and safety applications. This task is mostly based on the collection of particles with swabs, followed by thermal desorption into a vapor analyzer, usually a detector based on ion mobility spectrometry (IMS). While this methodology is well established for several civil applications, such as border control, it is still not efficient enough for various conditions, as in sampling rough and porous surfaces. Additionally, the process of thermal desorption is energetically inefficient, requires bulky hardware and introduces device contamination memory effects. Low-temperature plasma (LTP) has been demonstrated as an ionization and desorption source for sample preparation-free analysis, mostly at the inlet of a mass spectrometer analyzer, and in rare cases in conjunction with an ion mobility spectrometer. Herein, we demonstrate, for the first time, the operation of a simple, low cost, home-built LTP apparatus for desorbing non-volatile analytes from various porous surfaces into the inlet of a handheld IMS vapor analyzer. We show ion mobility spectra that originate from operating the LTP jet on porous surfaces such as asphalt and shoes, contaminated with model amine-containing organic compounds. The spectra are in good correlation with spectra measured for thermally desorbed species. We verify through LC-MS analysis of the collected vapors that the sampled species are not fragmented, and can thus be identified by commercial IMS detectors.