Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/138601
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dc.titleGOLD NANOSTARS AS A SURFACE ENHANCED RAMAN SPECTROSCOPY (SERS) SUBSTRATE FOR BIOSENSING APPLICATIONS
dc.contributor.authorHE SHUAI
dc.date.accessioned2018-01-30T18:00:20Z
dc.date.available2018-01-30T18:00:20Z
dc.date.issued2017-08-24
dc.identifier.citationHE SHUAI (2017-08-24). GOLD NANOSTARS AS A SURFACE ENHANCED RAMAN SPECTROSCOPY (SERS) SUBSTRATE FOR BIOSENSING APPLICATIONS. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/138601
dc.description.abstractSurface-enhanced Raman spectroscopy (SERS) is a sensitive and specific technique for molecular identification, which overcomes the limitations of conventional Raman spectroscopy by generating high enhancement and low fluorescence and hence is desirable for biosensing applications. Colloidal gold nanoparticles are common SERS substrates and gold nanostars (AuNS) have been reported to exhibit superior SERS enhancement among various morphologies due to the presence of multiple sharp spikes serving as SERS “hotspots”. While seedless synthesis approach of AuNS is more facile and rapid compared to seed-mediated approach, little is known about the effect of synthesis parameters on the SERS enhancement. Therefore, there is a need to optimize the SERS enhancement of AuNS synthesized using a seedless approach by varying the synthesis parameters as well as other extrinsic properties. The optimized AuNS can be then immobilized on filter paper strips to form a flexible, cost-effective, biodegradable and disposable SERS substrate, which overcomes the limitations of conventional solid phase SERS substrates and enables easy and efficient sample collection process such as physical swabbing. Biosensing applications such as identification of human enterovirus 71 (EV71) virus and Protein Kinase A (PKA) have been realized using the optimized AuNS-based SERS substrates.
dc.language.isoen
dc.subjectSERS, gold nanostar, substrate, biosensing, optimization
dc.typeThesis
dc.contributor.departmentBIOMEDICAL ENGINEERING
dc.contributor.supervisorKAH CHEN YONG JAMES
dc.contributor.supervisorTAN KHAY MING EDDIE
dc.description.degreePh.D
dc.description.degreeconferredDOCTOR OF PHILOSOPHY
Appears in Collections:Ph.D Theses (Open)

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