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Enhancing sensitivity for surface pl...
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Alleyne, Colin James.
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Enhancing sensitivity for surface plasmon resonance biosensors using periodic structures and spectro-angular image analysis.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Enhancing sensitivity for surface plasmon resonance biosensors using periodic structures and spectro-angular image analysis./
作者:
Alleyne, Colin James.
面頁冊數:
162 p.
附註:
Source: Dissertation Abstracts International, Volume: 72-02, Section: B, page: 0946.
Contained By:
Dissertation Abstracts International72-02B.
標題:
Engineering, Electronics and Electrical. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NR68503
ISBN:
9780494685037
Enhancing sensitivity for surface plasmon resonance biosensors using periodic structures and spectro-angular image analysis.
Alleyne, Colin James.
Enhancing sensitivity for surface plasmon resonance biosensors using periodic structures and spectro-angular image analysis.
- 162 p.
Source: Dissertation Abstracts International, Volume: 72-02, Section: B, page: 0946.
Thesis (Ph.D.)--McGill University (Canada), 2010.
Surface plasmon resonance (SPR) is a phenomena whereby photons are made to couple energy to a surface electron density wave traveling on a metal-dielectric interface. The coupling occurs at a specific energy and momentum, collectively referred to as the resonance condition, causing a dip in the reflected light. The characteristics of the dip are a function of the material properties at the interface; therefore monitoring the dip provides information about the local surface environment. Recent years have seen a push in SPR technology towards miniaturization, increased sensitivity, high throughput and multimodal approaches. This thesis focuses on two methods for improving the performance of SPR biosensors.
ISBN: 9780494685037Subjects--Topical Terms:
626636
Engineering, Electronics and Electrical.
Enhancing sensitivity for surface plasmon resonance biosensors using periodic structures and spectro-angular image analysis.
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Source: Dissertation Abstracts International, Volume: 72-02, Section: B, page: 0946.
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Surface plasmon resonance (SPR) is a phenomena whereby photons are made to couple energy to a surface electron density wave traveling on a metal-dielectric interface. The coupling occurs at a specific energy and momentum, collectively referred to as the resonance condition, causing a dip in the reflected light. The characteristics of the dip are a function of the material properties at the interface; therefore monitoring the dip provides information about the local surface environment. Recent years have seen a push in SPR technology towards miniaturization, increased sensitivity, high throughput and multimodal approaches. This thesis focuses on two methods for improving the performance of SPR biosensors.
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First, SPR sensitivity is improved through the use of a surface plasmon bandgap structure. It is shown here that operating an SPR biosensor in angular interrogation mode near the edge of such a bandgap will result in a six fold increase in the sensitivity compared to SPR on a flat metallic surface under the same conditions.
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Second, a method for improving the detection limit is shown using a novel data analysis technique based on image processing. A multimodal surface plasmon interrogation technique is used to create a 2-D image of the spectro-angular dispersion from a surface; which is then used to extract information about the surface environment using an eigenvector analysis technique developed to exploit the spectro-angular information. Using the novel eigenvector technique, designated as the Double Projection Method (DPM), on the spectro-angular data results in refractive index estimates over a wide dynamic range with a theoretical detection limit of 5x10-9 refractive index units (RIU); which is superior to the current highest sensitivity phase-based methods. Experimental work shows the DPM method capable of monitoring biomolecular interactions with small molecular weight reactants (∼400 Daltons) in real-time with an achieved resolution of 2x10-6 RIU.
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