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Title: | Multifunctional solid@MOF nanohybrids toward surface-enhanced raman spectroscopy (SERS) and electrochemistry applications | Authors: | Sim, Howard Yi Fan | Keywords: | Science::Chemistry | Issue Date: | 2021 | Publisher: | Nanyang Technological University | Source: | Sim, H. Y. F. (2021). Multifunctional solid@MOF nanohybrids toward surface-enhanced raman spectroscopy (SERS) and electrochemistry applications. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/153614 | Abstract: | Solid-MOF nanohybrids are an emerging platform for applications in SERS detection, reaction monitoring and catalysis. However, current applications revolve either gas or liquid-based molecules, which deprive it for real-life multiphase applications. Notably, solid-MOFs have interfacial cavities where molecular interactions take place under the influence of both functional solid nanoparticles and MOFs. In this thesis, we address these challenges by designing multifunctional solid@MOF for SERS and electrochemical applications. In chapter 2, we showcase solid@MOF practicality in driving immiscible gas-liquid biphasic molecules with in-situ monitoring at ambient conditions. In chapter 3, we demonstrate real-time stand-off atmospheric monitoring where we integrate both remote detection and Raman spectroscopy to obtain the molecular fingerprints up to 10 m. In chapter 4 and 5, we exploit ZIF excellent gas sorbing ability and develop various metallic nanocatalyst@ZIF to drive ambient electrochemical nitrogen reduction. Finally, I end my thesis with a research summary and outlook for future work. | URI: | https://hdl.handle.net/10356/153614 | DOI: | 10.32657/10356/153614 | Schools: | School of Physical and Mathematical Sciences | 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: | SPMS Theses |
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Howard Thesis_Revised_thesis format.pdf | Sim, Howard Yi Fan Ph.D Thesis | 7.8 MB | Adobe PDF | ![]() View/Open |
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