Title page for etd-0721117-105129


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URN etd-0721117-105129
Author Tsung-Lun Tsai
Author's Email Address terry25879@yahoo.con.tw
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Department Electrical Engineering
Year 2017
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Non-Enzymatic Glucose Sensor with ZnO nanotubes/CuO Nanoparticles Composite
Date of Defense 2017-07-25
Page Count 119
Keyword
  • dip coating method
  • hydrothermal method
  • zinc oxide nanotubes
  • copper oxide nanoparticles
  • non-enzymatic glucose sensor
  • Abstract In this study, we primarily investigated the double-layered nanostructure of zinc oxide (ZnO) nanotubes and copper oxide (CuO) nanoparticles on ITO substrate for non-enzymatic glucose sensor. The variations of nanostructures for sensing applications have attracted much attention recently. Many studies show that multi-layered nanostructures have better performances than single one. We use RF sputtering system to deposit ZnO and CuO seed layers. ZnO nanotubes are grown by hydrothermal synthesis and etched by chemical solution. CuO nanoparticles are fabricated by a secondary hydrothermal method or dip coating. After the procedures, the devices with CuO nanoparticles/ZnO nanotubes /ITO are formed. We analyze the physical and electrical properties of the devices to improve the performances of glucose sensing.
    The experimental results show that the composite nanostructure of copper oxide grown with 20 mM solution by dip coating has the best sensing performances. The sensitivity is 3.2 mAmM-1cm-2 and the linear sensing range is 0.1mM-6.5mM and R2 value of 0.9925 at room temperature. The sensitivity of the device has been enhanced for more than 50%. Due to the composite structure, the device has larger surface area and substantially increases the contact area with the object. The high-performance glucose sensor can be applied in the detection of diabetes and development of the food industry.
    Advisory Committee
  • Ying-Chung Chen - chair
  • Shih-Fang Chen - co-chair
  • Cheng-Yu Ma - co-chair
  • Feng-Renn Juang - advisor
  • Files
  • etd-0721117-105129.pdf
  • Indicate in-campus at 5 year and off-campus access at 5 year.
    Date of Submission 2017-08-21

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