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    Development of MEMS-based chemical pre-concentrators with integrated sensing units for analysis of gas-phase volatile organic compounds

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    CARRON-THESIS-2015.pdf (4.751Mb)
    Date
    2015-07-22
    Author
    Carron, Christopher John
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    Abstract
    A MEMS-based micro thermal pre-concentration (μTPC) system for enhanced detection of gas phase volatile organic compounds (VOCs) is presented. The system implements a suspended membrane geometry, enhancing thermal isolation and enabling high temperature elevations even for low levels of heating power. The membranes have a large surface area-to-volume ratio but low thermal mass (and therefore, low thermal time constant), with arrays of 3-D high aspect-ratio features formed via DRIE of silicon. Integrated onto the membrane are sets of diffused resistors designed for performing thermal desorption (via joule heating) and for measuring the temperature elevation of the device due to the temperature-dependent resistivity of doped silicon. The novel system features integrated real-time chemical sensing technology, which allows for reduced sampling time and a reduced total system dead volume of approximately 10 μL. The system is capable of operating in both a traditional gas-flow setup and also in a static atmosphere which requires no external fluidic flow system, thereby enabling novel measurement methods and applications. The ability to operate without a forced-flow fluidic system is a distinct advantage and can considerably enhance the portability of a sensing system, facilitating deployment on mobile airborne platforms as well as long-term monitoring stations in remote locations. Finally, the real-time measurement capabilities of the integrated chemical sensors allow for transient analysis of thermally generated signals, which has been demonstrated to improve analyte discrimination for VOCs without the need for a separation column or external fluidic system Initial tests of the system have demonstrated a pre-concentration factor of 50% for toluene.
    URI
    http://hdl.handle.net/1853/55538
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    • Georgia Tech Theses and Dissertations [23877]
    • School of Electrical and Computer Engineering Theses and Dissertations [3381]

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