Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/184694
Title: The design of optical nanocavities for single-molecule detections with multiple fluorescence probes
Authors: Zhou, Yixiao
Keywords: Engineering
Issue Date: 2025
Publisher: Nanyang Technological University
Source: Zhou, Y. (2025). The design of optical nanocavities for single-molecule detections with multiple fluorescence probes. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/184694
Abstract: Single-molecule detection plays a crucial role in advancing biomedical research and clinical diagnostics, providing high sensitivity and specificity that conventional techniques lack. This dissertation presents the design and development of an innovative optical nanocavity system aimed at achieving efficient single-molecule detection, with a focus on microRNA (miRNA) detection, which serves as a valuable biomarker for early disease diagnosis, particularly in cancer. The primary challenge addressed by this work is the low sensitivity and signal-to-noise ratio in existing detection methods. To overcome this, a novel optical nanocavity structure composed of dielectric distributed Bragg reflector (DBR) mirrors and silver nanoparticles (AgNPs) was designed. The DBR mirrors enhance the cavity’s quality factor, while the AgNPs amplify fluorescence signals via localized surface plasmon resonance (LSPR). This combination enables the detection of miRNAs at concentrations as low as 100 femtomolar (fmol), offering a significant improvement in sensitivity. The system's ability to selectively amplify fluorescence signals while minimizing background noise was validated experimentally through the detection of multiple miRNA targets. In the future, the proposed nanocavity can be integrated into a portable and user-friendly sensing platform to enable self-testing and real-time diagnostics. The use of this platform has the potential to revolutionize personalized medicine by providing a cost-effective solution for detecting low-abundance biomarkers in clinical samples.
URI: https://hdl.handle.net/10356/184694
Schools: School of Electrical and Electronic Engineering 
Research Centres: Centre for Biodevices and Bioinformatics
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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