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Volatile Organic Compound Odor Signature Modeling

Description:

OBJECTIVE: Research and develop methods, models and algorithms for use in portable sensing platforms to predict the transport and dispersion of volatile organic compounds (VOCs) emitted from individuals of interest and their related threat activities. DESCRIPTION: Background & Significance - A growing body of discoveries in molecular signatures have revealed that VOCs, the small molecules associated with an individual"s odor and breath, may be monitored to reveal the identity and presence of a unique individual as well as an indicator of certain activities. Animals use VOC recognition to distinguish between friend, foe, or prey. Dogs can recognize specific odors related to some disease states. Medical practitioners can also recognize characteristic odors of certain disease states, i.e., ketosis. The ability to find and track individuals using VOC signatures would greatly enhance DoD capability to defeat asymmetric threats. These individuals often hide in civilian populations emerging only to strike warfighters and then retreat behind their civilian shield. Current policy requires our forces to avoid inflicting collateral damage on innocent civilians. As such, it is necessary to improve our ability to identify and track individuals and their threat activities. The ability of animals to identify and track individuals using scent has led to an interest in developing a similar signals intelligence capability. As highlighted in a review article by our group (Kramer, R., Grigsby, C., 2012), recent research in odor-based sensing has shown that this technology provides a means whereby individuals and their threat activities may be identified through unique combinations of VOCs emitted by the body. Development of the capability to predict the transport and dispersion of VOCs in both interior spaces and the environment will assist in defining the technical requirements and operational application of VOC-based sensors with the goal of the generation of a"reverse"modeling capability to backtrack individuals and activities of interest. The current state-of-the-art requires an informant or another person to be physically close to the person of interest to positively identify him. Physical disguises may often make identification of individuals very difficult. The use of VOC signature data to identify a person of interest has potential to overcome any physical disguises and the need to put friendly forces at risk by being in close proximity in hostile territories. The hypothesis is that operational environment transport and dispersion modeling of human-emitted VOCs may be used to provide a temporal characterization for an individual"s presence at a specific location. This is supported by the fact that volatile organic compound signatures have been proven capable of identifying unique individuals. Further, modeling and simulation of the VOC transport and dispersion process may be employed to support this research hypothesis. PHASE I: Successful completion of Phase I will require empirically derived physical characteristics for a minimum of twelve specified VOCs, evaluation of potential atmospheric chemical breakdown/reactivity, and development of transport and dispersion (T & D) models of the supplied VOC pattern in both interior spaces and the environment. PHASE II: Research, analyze, and define volatile organic compound sensitivity and specify sensing requirements for hand-held detection, using both single point, enhanced"E-nose"type detection as well as multiple detectors. Research and develop models and algorithms to backtrack an individual"s past location. This phase will culminate with transition of algorithms and models into a platform independent language for integration into portable sensor device prototypes. PHASE III: Successful commercialization of this research will require incorporation of the developed models and algorithms, i.e., empirically derived VOC characteristics and developed inverse modeling capability for back-tracking the VOC source spatially and temporally, into a supplied prototype sensing platform. REFERENCES: 1. Kramer, R.M., Grigsby, C.C. Analytical determination and detection of individual odor signatures. 2012. Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring II; and Biometric Technology for Human Identification IX. Proc. SPIE 8371. 2. Baines, W.D., James, D.F. Evaporation of a droplet on a surface. Ind. Eng. Chem. Res. 1994. 411-416. 3. Starov, V.M., Zhdanov, S.A., Kosvintsev, S.R., Sobolev, V.D., Velarde, M.G. Spreading of drops over porous substrates. Advances in Colloid and Interface Science. 2003. 123-158. 4. Reis, N.C., Griffiths, R.F., Mantle, M.D., Gladden, L.F., Santos, J.M. MRI investigation of the evaporation of embedded liquid droplets from porous surfaces under different drying regimes. Internation Journal of Heat and Mass Transfer. 2006, 951-961. 5. Gallagher, M., Wysocki, C. J., Leyden, J. J., Spielman, A. I., Sun, X., & Preti, G. Analyses of volatile organic compounds from human skin. British Journal of Dermatology. 2008. 159, 780-791. 6. Zlatkis, A., R. S. Brazell, et al. The role of organic volatile profiles in clinical diagnosis. Clin Chem. 1981. 27(6): 789-97. 7. Boyse, E., G. Beauchamp, et al. The genetics of body scent. Trends Genet. 1987. 3: 97-102.
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