The work presented in this thesis details new capabilities and applications of a fluorescence-based microsphere array vapor sensing system developed in the Walt Laboratory over a period of several years. The system is designed on the principles of mammalian olfaction in that several cross-reactive and non-specific sensors are integrated into a high density array format. The system responds to an analyte vapor in a cross-reactive manner generating a multi-dimensional signal that can be used to train a pattern recognition program to identify subsequent exposures of the array to learned vapors.
Several ways in which the classification accuracy of this system can be improved are explored. New sensors based on porphyrin compounds were developed and their vapor sensing properties were characterized. This new class of sensors was systematically evaluated within the context of existing sensor types to determine their effectiveness in expanding the range of chemical compounds that can be reliably detected and classified. A second route to improving the classification accuracy of the system involves implementing a biomimetic data processing scheme. This method emulates the biological process of active sampling, or 'sniffing', and has been shown to reduce the number of errors in classification when the system is challenged with a broad range of chemical species. Finally, the ability to monitor the entire fluorescence spectrum from many individual sensors offers the opportunity to optimize the discrete wavelengths at which a response is observed. A method to collect this spectrum in a highly parallel fashion with excellent temporal resolution has been developed and is shown to improve the classification accuracy when information from multiple wavelengths is incorporated into a response matrix.
An exploration into new applications of this system is presented. Specifically, a preliminary investigation into using this device during the early stages of a fire investigation is described. The results of this investigation show that the system is capable of correctly detecting and classifying three types of ignitable liquids when presented in a realistic sample matrix. The design and construction of a portable device is also described and the results of field experiments are presented. The results of these studies demonstrate the basic functionality of the portable device and establish its usefulness in the detection of petroleum distillates in the ambient environment.
|Advisor:||Walt, David R.|
|Commitee:||Rybak-Akimova, Elena V., Sotzing, Gregory A., Utz, Arthur L.|
|School Location:||United States -- Massachusetts|
|Source:||DAI-B 70/11, Dissertation Abstracts International|
|Keywords:||Microsphere array, Pattern recognition, Vapor sensing|
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