学位论文详细信息
Development of a bulk acoustic resonator sensing platform for cancer biomarker detection
Surface mount resonator;Cancer biomarker;Zinc oxide;Bulk acoustic wave
Mobley, Stephen J. ; Bhatti, Pamela Electrical and Computer Engineering Hunt, William D. Brand, Oliver Doetsch, Paul Kenney, James S. ; Bhatti, Pamela
University:Georgia Institute of Technology
Department:Electrical and Computer Engineering
关键词: Surface mount resonator;    Cancer biomarker;    Zinc oxide;    Bulk acoustic wave;   
Others  :  https://smartech.gatech.edu/bitstream/1853/56162/1/MOBLEY-DISSERTATION-2015.pdf
美国|英语
来源: SMARTech Repository
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【 摘 要 】

Cancer is one of the leading causes of death for patients within the United States and throughout the world. When diagnosed in early growth stages, tumors (regions of uncontrolled cell division) can be more effectively treated and patients are more likely to survive. Therefore, the development of screening technology for early detection of cancer is essential to improve patient survival rates and serves as the motivation for this work. The objective of this dissertation is the design and implementation of a sensing platform for the detection of cancer biomarkers within aqueous patient samples. The system’s transducer is based on previously developed zinc oxide (ZnO) bulk acoustic wave (BAW) resonators that are capable of exciting multiple types of acoustic modes. Chapter 1 presents the motivation for this work along with a short review of gravimetric biosensors used in aqueous applications. Chapter 2 focuses on the history, theoreticalderivation, and fabrication protocol for the system transducers and array configuration. In Chapter 3, the Universal Serial Bus (USB) is examined as a potential radio frequency bus for device characterization of MEMs devices. Chapter 4 presents the optimization of a module design for isolating the circuitry from the fluidics pathways for sample exposure. Combining the work of the previous chapters, Chapter 5 validates the ability of the designedsystem to serve as a biosensing platform. Each individual sensor is functionalized with antibodies selectively binding the desired biomarker. Lastly, Chapter 6 demonstrates a protocol for extracting features from raw sensor data to develop classification models. Thus, providing diagnostic information about the sample exposed to the device.

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