Mass Spectrometry Vapor Analysis for Improving Explosives Detection Canine Proficiency
Abstract
Canines remain the gold standard for explosives detection in many situations, and there is an ongoing desire for them to perform at the highest level. This goal requires canine training to be approached similarly as scientific sensor design. Developing a canine training regimens is made challenging by a lack of understanding of the canines odor environment, which is dynamic and typically contains multiple odorants. Existing methodology assumes that the handlers intention is an adequate surrogate for actual knowledge of the odors cuing the canine, but canines are easily exposed to unintentional explosive odors through training material cross-contamination. A sensitive, real-time (~1 sec) vapor analysis mass spectrometer was developed to provide tools, techniques, and knowledge to better understand, train, and utilize canines. The instrument has a detection library of nine ex-plosives and explosive-related materials consisting of 2,4-dinitrotoluene (2,4-DNT), 2,6-dinitrotoluene (2,6-DNT), 2,4,6-trinitrotoluene (TNT), nitroglycerin (NG), 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), penta erythritol tetranitrate (PETN), tri-acetone triperoxide (TATP), hexamethylene triperoxide diamine (HMTD), and cyclohexanone, with detection limits in the part-per-trillion to part-per-quadrillion range by volume. The instrument can illustrate aspects of vapor plume dynamics, such as detecting plume filaments at a distance. The instrument was deployed to support canine training in the field, detecting cross-contamination among training materials, and developing an evaluation method based on the odor environment. Support for training material production and handling was provided by studying the dynamic headspace of a non-explosive HMTD training aid that is in development. These results supported existing canine training and identified certain areas that may be improved.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 10, 2017
- Accession Number
- AD1032196
Entities
People
- Alla Ostrinskaya
- Geoffrey P. Geurtsen
- Jude A. Kelley
- Roderick R. Kunz
- Ta-Hsuan Ong
- Ted Mendum
Organizations
- MIT Lincoln Laboratory