Monitoring biological systems is crucial in healthcare, driving the need for reliable and noninvasive solutions. The proliferation of unverified drugs in the market necessitates reliable methods for their detection and identification, especially amidst advancements in pharmaceuticals. Plasmonic biosensors emerge as a great platform for ultra-sensitive detection, identification, and manipulation of biomolecular systems. This dissertation report addresses the critical need for precise detection and monitoring of biomolecules and drugs, presenting innovative solutions through the design of a plasmonic biosensor to tackle challenges in sensitivity, selectivity, and label-free detection and identification. We introduce a robust and tunable, cavity-integrated plasmonic nanopatterned sensor that exhibits superchiral light in the infrared domain for ultrasensitive detection of chiral molecular concentrations and enantiomeric excesses. The multispectral capability of this system is further harnessed to generate unique chiral fingerprint-based barcodes for the identification of diverse chiral drugs and biomolecules. We further discuss and demonstrate results for a surface-modified plasmonic biosensor operating in the visible-near-infrared realm in detecting viral biomarkers and neurotransmitters directly from complex physiological environments. The system, on coupling with a microfluidic flow setup allows sensitive, selective and rapid detection without requiring complex pre-processing or sample preparation steps. We discuss additional applications of the unique plasmonic sensor, utilizing the property of tunable superchirality to create a dynamic chirality tracking system operating in the near infrared for real-time monitoring of protein dynamics. These techniques aim to revolutionize bio-detection, chiral differentiation, and sorting processes, having extensive applications in medical research and pharmaceutical industries.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2023-1154 |
| Date | 01 January 2024 |
| Creators | Biswas, Aritra |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Thesis and Dissertation 2023-2024 |
| Rights | In copyright |
Page generated in 0.0022 seconds