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Plasmonic Interferometry: A New Approach toward Highly-Sensitive Multispectral Biochemical Detection

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Abstract:
Surface plasmon polaritons are hybrid electron-photon modes confined at a metal/dielectric interface. The combination of highly localized electronic waves and propagating optical waves gives the surface plasmon wave unique characteristics, which have attracted growing interest over the past decades and started the research field of "plasmonics". A sub-field in plasmonics, named "plasmonic interferometry", which focuses on the interference effects of surface plasmon waves, is hereby presented. Specifically, in this thesis, I discuss the design of plasmonic interferometers for biochemical sensing, utilizing the unique features of surface plasmons. A multispectral plasmonic refractometer and a highly-sensitive biochemical detector are built upon plasmonic interferometry, taking advantage of its susceptibility to optical properties of the interface materials. As a proof of concept, the detector is capable of sensing glucose concentrations down to the physiological levels in saliva. Its sensitivity and specificity is further enhanced when coupled to a dye chemistry. I also explore an alternative scheme to achieve detection selectivity by functionalizing the device surface with specific antibodies. In addition, plasmonic interferometry in some other geometries are investigated, e.g., a generalized circular geometry. Finally, with light emitters directly embedded in the subwavelength cavities of plasmonic interferometers, active plasmonic interferometry is accomplished, which successfully replaces the previous rigid requirements for a coherent light source. Accordingly, plasmonic interferometry has the great potential for the development of a new generation of multiplexed biochemical sensors that are compact, multi-spectral and ultra-sensitive.
Notes:
Thesis (Ph.D.)--Brown University, 2017

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Citation

Feng, Jing Feng, "Plasmonic Interferometry: A New Approach toward Highly-Sensitive Multispectral Biochemical Detection" (2017). Electrical Sciences and Computer Engineering Theses and Dissertations. Brown Digital Repository. Brown University Library. https://doi.org/10.7301/Z0RV0M4R

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