Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/164768
Title: | Surface-enhanced Raman scattering (SERS) spectroscopy platforms for enhanced detection at the nanobio interface: from metabolites to microorganisms | Authors: | Leong, Shi Xuan | Keywords: | Science::Chemistry | Issue Date: | 2023 | Publisher: | Nanyang Technological University | Source: | Leong, S. X. (2023). Surface-enhanced Raman scattering (SERS) spectroscopy platforms for enhanced detection at the nanobio interface: from metabolites to microorganisms. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/164768 | Abstract: | Surface-enhanced Raman scattering (SERS) spectroscopy is a powerful spectroscopic technique that enhances molecules’ weak Raman signals for ultrasensitive identification and quantification. However, molecule detection at the nanobio interface is hindered by challenges including poor surface affinities, complex sample matrices, and analogous chemical structures. In this thesis, we overcome these roadblocks by synergizing designer plasmonic platforms with emerging strategies to expand the analyte scope, ranging from small-molecule metabolites to microorganisms. Here, we successfully design direct enantiospecific nanoparticle-analyte interactions for label-free, generic chiral differentiation. We also leverage pattern-based recognition of differential probe-analyte interactions to distinguish small-molecule metabolites, both as individual molecules and in complex mixtures, such as the human breath, as well as microorganisms with complex surface biomolecular architectures. We thus showcase the immense potential of the novel and strategic combination of various techniques in advancing SERS beyond the current state-of-the-art toward real-life detection of a broader analyte scope. | URI: | https://hdl.handle.net/10356/164768 | DOI: | 10.32657/10356/164768 | Schools: | School of Chemistry, Chemical Engineering and Biotechnology | Rights: | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | CCEB Theses |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Amended Thesis - Leong Shi Xuan.pdf | 8.51 MB | Adobe PDF | ![]() View/Open |
Page view(s) 50
541
Updated on Feb 11, 2025
Download(s) 10
414
Updated on Feb 11, 2025
Google ScholarTM
Check
Altmetric
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.