Date of Award
Electrical and Computer Engineering
Concentric Electrode, Dual Inverted Mesa, Gas Sensor, Multiple Gas Detection, QCM, Quartz Crystal Microbalance
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Lung Cancer is one of the most deadly diseases which claim millions of lives all around the world every year. One of the major reasons that make the treatment process of lung cancer hard is that the patients are diagnosed only during the later stages. Lung cancer patients exhales volatile organic compounds in their breath in low concentration even during the early stages of the disease. There are many gas sensors available to detect these volatiles. However, there are certain disadvantages which make most of the conventional gas sensors unsuitable for early detection. Quartz crystal microbalance (QCM) is one of the promising candidates for volatile organic compounds detection. This thesis describes the design and analysis of the high-frequency quartz crystal microbalance sensor array with a novel concentric electrode and dual inverted mesa structure. Conventional QCM sensors are limited with circular electrodes and single channel design which limits the sensing ability. The proposed QCM sensor array has advantages of a uniform displacement profile with the concentric electrodes and multiple channels on a high frequency monolithic quartz substrate without interference with the dual inverted mesa design. This high frequency multiple channels make the multiple gas detection feasible. Therefore, in this thesis the critical design parameters of this proposed design are analyzed and optimized through a comprehensive finite element analysis in COMSOL Multiphysics and analytical modelling. In addition, the interference between multiple QCM channels has been further eliminated. Furthermore, the fabrication procedure for the proposed high frequency QCM gas sensor array has been proposed and analyzed.
Joseph, Aashish, "Design and Analysis of High-Frequency Quartz Crystal Microbalance Sensor Array with Concentric Electrodes and Dual Inverted Mesa Structure for Multiple Gas Detection" (2019). Electronic Theses and Dissertations. 8168.