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Title: Development of a MEMS-based Resonant and Impedimetric Multivariate Sensor for the Speciation and Quantification of Volatile Organic Compounds
Committee:
Dr. Oliver Brand, ECE, Chair, Advisor
Dr. Azadeh Ansari, ECE
Dr. Callie Hao, ECE
Dr. Farrokh Ayazi, ECE
Dr. Peter Hesketh, ME
Abstract: This work demonstrates the design and development of a novel MEMS-based multivariate gas microsensor for identificaiton of various volatile organic compounds (VOCs) and their subsequent concentration quantification. This multiviariate gas sensor utilizes a highly-senstive underlying resonant gravimetric microcantilever in combination with an interdigitated electrode (IDE) structure underneath a single polymeric sensing film to provide both gravimetric and impedimetric analysis of gaseous analystes in the environment. Mutlivariate analysis techniques including dispersion anlaysis and machine learning methods were applied to both the steady-state and transient sensor response data enabling both qualtitative and qunatitiative means of discriminaiton of VOCs. Methods were developed to enable concentration-independent selecitivty enhancement while drastically reducing the overall sensor response time. The limit of detection for concentration quantification was reduced through improvments in the thermal stability of the underlying gravimetric resonant sensor using passive thermal compensation techniques in the device design and fabrication. High dynamic range of the sensor was enabled through a unique resonant microcantilever design and sensing material selectio. Overall, this 200-micron sized microgas sensor provides enhanced selectivity, reduced response times of a diffusion-limited gas sensor, and impoved limit of detection and dyanmic range enabling a new type of miniturized sensing element for intelligent gas sensing systems of the future.
