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    Theoretical and Experimental Characterization of Time-Dependent Signatures of Acoustic Wave Based Biosensors

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    Date
    2006-07-13
    Author
    Lee, Sang Hun
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    Abstract
    The object of this thesis research is to facilitate the appraisal and analysis of the signatures of the modern acoustic wave biosensors, as well as to improve the experimental methodology to enhance sensor performance. For this purpose, both theoretical characterization of acoustic wave sensor signatures and experimental studies for the most frequently used acoustic wave biosensors, the liquid phase QCM (quartz crystal microbalance) and the vapor phase SAW (surface acoustic wave) sensors, are presented. For the study of SAW vapor phase detection, the author fabricated different types of two-port SAW resonator sensors on quartz substrates and designed and performed a significant number of detection experiments. These were conducted both with calibrated or known target samples under laboratory conditions at Georgia Tech Hunt Lab and with samples of unknown concentrations such as seized crack cocaine (courtesy of Georgia Bureau of Investigation, GBI) to see the sensors capability to work in the field conditions. In addition, the dependence of the SAW sensor signatures on specific locations of the surface perturbation was investigated to account for some observed abnormal responses. Finally, a novel approach to classify and visualize chemically analogous substances is introduced. The author expects that the thesis work herein may contribute to the study of the modern acoustic wave biosensors which includes but is not limited to: the establishment of underpinning theory that will aid in the evaluation of the signatures; the practical aspects of design and fabrication of SAW devices specific to the vapor phase immunoassay; the development of efficient experimental methodologies; the strategic immobilization of a biolayer on SAW resonator based biosensors; and, the acquisition of reference data for the development of commercial acoustic wave sensors.
    URI
    http://hdl.handle.net/1853/11631
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    • Georgia Tech Theses and Dissertations [23877]
    • School of Electrical and Computer Engineering Theses and Dissertations [3381]

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