Thesis - Open Access
Master of Science (MS)
Electrical Engineering and Computer Science
acetone and ethanol interaction with graphene and PEG, Graphene adsorption, Langmuir, BET, Freundlich, LOD, Molecular imprinted filter, suspensionless graphene solution
Wellness sensor technology is an emerging diagnostic test research field, which mostly deal with the point of care of the patients in the recent days. Due to the lack of awareness from the patients, most diseases cannot be detected in due time. This led to worse conditions, such as diabetic and alcoholic syndrome. Therefore, many research groups have been working to develop portable sensor devices that can track serious diseases. These include diabetic and alcoholic biomarkers in breathing. These devices have very high selectivity and reliability. However, the major limitation of biomarkers is that it deals with the bio-molecular based sensing mechanism. Extensive challenges exist in the selectivity and reliability of breathing sensors. These require development of proper materials and effective detection methods. Thus, selection of proper materials, correct sensing parameters, effective device architecture and simple fabrication processing are substantially critical. The goal of this work is to develop graphene based breathing sensors with high selectivity and sensitivity using a novel molecular imprinted filtering technique. The sensors have various applications including Point of Care Testing (POCT) device for personalized home and clinical use in early detection of diabetic and alcoholic patients. Different fabrication procedures were used to optimize the sensor performance. The optimized results demonstrate that a proper biomarker molecule imprinting process could selectively detect diabetes and alcohol. The graphene layer was optimized by maintaining spray coating time, pattern and distance between the substrate and spray coater. Graphene adhesion to the substrate was also improved using polyvinyl pyrrolidone. The molecular imprinting filter made on top of the graphene layer improved the performance of acetone and ethanol molecule detection, indicated by the change of resistance in the graphene layer. The sensors showed poor performance for long-time exposure (> 10 second) due to ambient molecules and moisture. However, the sensor characteristics were significantly improved for short exposing time (3-4 second) due to the optimization in the thickness of the filtering layer and sensing layer.
Includes bibliographical references (pages 60-67).
Number of Pages
South Dakota State University
In Copyright - Educational Use Permitted
Bhuiyan, Md. Saleh Akram, "Development of Highly Sensitive and Selective Breathing Sensors Using Molecular Imprinted Filtering for Diabetic and Alcoholic Patients" (2017). Theses and Dissertations. 1702.