Sampling and Sensing Methodology

In another study, Darrach et al. [2] reported that samples collected near intact UUXO targets contained traces of explosives at up to parts per billion (ppb) concentration levels. The samples were analyzed in the laboratory, using solid-phase microextraction (SPME) to extract target analytes from the samples. The samples were then processed using a reversal electron attachment detection (READ) technique. If the levels of contamination found in these studies are representative of that emanating from most UUXO, the implication is that sensitive chemical sensors such as the SeaDog may be useful for detecting UUXO. 

The SeaDog sensor utilized in this work is capable of near real-time detection of low concentrations of explosives in water. The sensor utilizes novel sensing materials originally developed by collaborators at MIT. These materials are fluorescent polymers that are highly emissive when deployed as solid-state thin films. When the polymers interact with nitroaromatic explosives such as TNT, the fluorescence is quenched [3-5], The response of these materials to target analytes 

The underwater sensor platform is derived from the Fido explosives vapor sensor, originally developed under the Defense Advanced Research Projects Agency (DARPA) Dog s Nose Program. The vapor sensor, whose operation is discussed in Chapters 7 and 9 and in other publications [7-9], was developed for the task of landmine detection. The underwater adaptation of the sensor is very similar to the vapor sensor. In the underwater implementation of the sensor, thin films of polymers are deposited onto glass or sapphire substrates. The emission intensity of these films is monitored as water (rather than air) flows past the substrate. If the concentration of TNT in the water beings to rise, the polymer will exhibit a measurable reduction in fluorescence intensity. The reduction in emission intensity is proportional to the concentration of target analyte in the water. Because the sensor is small, lightweight, and consumes little power, it proved to be ideal for deployment on autonomous platforms. 

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