Improving Detection and Identification Methods for Volatile Organic Explosives

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Although numerous chemical detection methods have been posited and tested for portability and detection of explosives, to date no method has solved the simultaneous issue of speed, reliability, selectivity and sensitivity. In order to advance the chemical and biological detection of explosives as screening tools in search areas, it is necessary to understand the key volatile organic compounds (VOCs) produced and detected by explosives. This thesis aimed to investigate a range of chemical detection methods, including portable and benchtop, to gain a better understanding of the VOCs produced in the headspace of commonly utilised explosives. The first stage of this project focused on the investigation of a previously reported capillary electrophoresis (CE) system coupled to an oscilometric detector (C4D) but with limited success. The second stage of this project focused on the study of commercially-available techniques. A lab-on-a-chip (LOC) was repurposed and successfully used to detect explosive residues in liquid and vapour samples. The Agilent 2100™ Bioanalyzer showed recovery rates of 29, 45 and 75 % for the three nitrate explosives investigated. A transportable gas chromatography-mass spectrometry (GC-MS) system was also tested, however due to several issues presented the instrument was not able to perform headspace analysis. Instead, a benchtop GC-MS and a two dimensional gas chromatograph (GC×GC) coupled to a time of flight mass spectrometer (TOFMS) were investigated. The conventional GC-MS method proved to be inefficient for headspace profiling, whereas the GC×GC-TOFMS was successful in separating and detecting the key VOCs from explosive samples. 2,3-dimethyl-2,3-dinitrobutane (DMDNB), 2,4-dinitrotoluene (DNT), and 1,3-dinitrobenzene (DNB) were identified as the most significant VOCs and subsequently used in the final stage of this project to compare the chemical detection methods with biological detection methods. Accredited explosive detection dogs (EDDs) were exposed to varying concentrations of the three significant VOCs. The study demonstrated that the dogs increased their response over time and with exposure to the standards, demonstrating a learning curve to the target odour. This study has demonstrated comparable sensitivity between EDDs and the benchtop GC×GC-TOFMS method, however canines are still considered the most effective real-time method for screening of explosives, due to their speed and selectivity over large areas. This thesis has advanced our understanding on the VOCs that comprise the odour profile of explosives and will assist with the future enhancement of chemical and biological detection methods.
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