An ongoing weapons of mass destruction (WMD) threat is the aerosolization of low-volatility chemical weapons agents (CWAs) such as the V-series nerve agents, Novichoks [1], and pharmaceutical-based agents (PBAs) e.g. fentanyl and other high-potency opioids [2]. These materials are liquids or solids at room temperature and generally have extremely low vapor pressures, rendering them difficult, if not impossible, to detect with conventional vapor-only detection systems. If these materials are aerosolized, they can disperse over broad geographical areas posing an immediate risk to individuals encountering them while airborne. Upon settling, a wide swath of persistent agent contamination may be left behind, posing an on-going surface contact threat or re-aerosolization risk. Field detection of toxic aerosols remains a significant challenge for chemical detectors. Most of the existing hand-held chemical detection technologies are not equipped to screen ambient air samples for the presence of aerosolized threats, leaving a capability gap among the most widely deployed point sensing technologies. Recently, 908 Devices released an aerosol module (the ‘Aero’) that is compatible with the MX908 handheld mass spectrometer. The combination of the aerosol module with portable mass spectrometry enables the detection of aerosolized threats within seconds at concentration levels that enable warfighters and first responders to take protective action quickly and minimize the impact from this alternative threat class.
Analytical technologies including infrared, Raman, and X-ray fluorescence have seeing increasing in-field application over the last 15 years due primarily to advances in miniaturization and on-board embedded analytics focused on giving actionable answers to non-scientist operators. Though a long-time favorite in the analytical laboratory, mass spectrometry has taken longer to attain widespread field adoption largely due to challenges surrounding device portability. In the last few years, mass spectrometry has evolved to a truly handheld state and has continued to broaden its field capabilities and is now seeing significant in-field use as a result. In this presentation we will review state of the art in microscale ion trap systems and present test data from a variety of CBRNE relevant examples, including results generated using a sampling module designed to detect aerosolized threats
In the operational airport environment, the rapid identification of potentially
hazardous materials such as improvised explosive devices, chemical warfare agents and
flammable and explosive liquids is increasingly critical. Peroxide-based explosives pose
a particularly insidious threat because they can be made from commonly available and
relatively innocuous household chemicals, such as bleach and hydrogen peroxide.
Raman spectroscopy has been validated as a valuable tool for rapid identification of
chemicals, explosives, and narcotics and their precursors while allowing "line-of-sight"
interrogation through bottles or other translucent containers. This enables safe
identification of both precursor substances, such as acetone, and end-products, such as
TATP, without direct sampling, contamination and exposure by security personnel.
To date, Raman systems have been laboratory-based, requiring careful operation
and maintenance by technology experts. The capital and ongoing expenses of these
systems is also significant. Recent advances in Raman component technologies have
dramatically reduced the footprint and cost, while improving the reliability and ease of
use of Raman spectroscopy systems. Such technologies are not only bringing the lab to
the field, but are also protecting civilians and security personnel in the process.
In recent years a number of analytical devices have been proposed and marketed specifically to enable field-based material identification. Technologies reliant on mass, near- and mid-infrared, and Raman spectroscopies are available today, and other platforms are imminent. These systems tend to perform material recognition based on an on-board library of material signatures. While figures of merit for traditional quantitative analytical sensors are broadly established (e.g., SNR, selectivity, sensitivity, limit of detection/decision), measures of performance for material identification systems have not been systematically discussed. In this paper we present an approach to performance characterization similar in spirit to ROC curves, but including elements of precision-recall curves and specialized for the intended-use of material identification systems. Important experimental considerations are discussed, including study design, sources of bias, uncertainty estimation, and cross-validation and the approach as a whole is illustrated using a commercially available handheld Raman material identification system.
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