| Summary: | 碩士 === 國立中正大學 === 機械工程學系暨研究所 === 103 === This study focuses on improving the performance of injction-molded guided-mode resonance biosensors. Two main topics are included: (a) enhancement of sensitivity via-subsurface cavities, and (b) development of low-cose, high-sensitivity low-cost, label-free intensity-resolved optical signal acquisition platform.
On the topic of sensitivity enhancement, sub-surface cavities are created at the interface between the waveguide and cyclic olefin copolymer (COC) substrate by adjusting the sputtering parameters. As the oxygen content increases in the sputtering process, the mean cavity size is increased, and the sensitivity is enhanced by 221%, in comparison to a reference GMR sensor without a cavities. Finite-element-method simulations are performed to analyze the effect of cavities. The results show that the cavities decrease the effective refractive index of the medium beneath the waveguide and significantly redistribute the resonance mode profile. As a result, the evanescent wave is extended toward the sensing area and the penetration depth is increased. In addition, we find the relationship between the refractive index of cavity layer and the sensitivity is nonlinear. As the refractive index of cavity layer approaches that of analyte, the sensitivity is significantly enhanced.
For the development of label-free intensity-detection signal acquisition platform, the detection is built based on transmission experiments using a low-cost green light-emitting diode as the light source, and a photodetector as the detecting unit. With the spectrum-limited light source, the intensity of transmission light becomes convolution of LED and GMR transmission spectra, successfully converting the GMR shifts to intensity changes. Our experiments show that a refractive index resolution of 7.58×〖10〗^(-5) RIU is achieved. This present investigation demonstrates a low-cost, label-free, high sensitivity bio-sensing platform for practical applications in food adulteration, bio-medical and chemical detection.
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