Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/139072
DC Field | Value | |
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dc.title | DEVELOPMENT OF AUTOMATED GREEN SAMPLE PREPARATION METHODS FOR ENVIRONMENTAL AQUEOUS CONTAMINANTS | |
dc.contributor.author | SHALENE GOH XUE LIN | |
dc.date.accessioned | 2018-02-28T18:00:39Z | |
dc.date.available | 2018-02-28T18:00:39Z | |
dc.date.issued | 2017-08-04 | |
dc.identifier.citation | SHALENE GOH XUE LIN (2017-08-04). DEVELOPMENT OF AUTOMATED GREEN SAMPLE PREPARATION METHODS FOR ENVIRONMENTAL AQUEOUS CONTAMINANTS. ScholarBank@NUS Repository. | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/139072 | |
dc.description.abstract | This dissertation presents the developments and applications of miniaturised sample preparation methods, coupled with liquid chromatography-tandem mass spectrometry for environmental analysis on emerging contaminants of concerns. They are simple, rapid, environmental-friendly and cost-effective, compared to conventional methods which require large volumes of sample and organic solvent, and intensive labour. Studies on membrane-mediated liquid-phase microextraction, such as the development of novel in-house fabricated extraction devices using polypropylene hollow fiber and membrane, and online solid-phase extraction are discussed. The thesis also focuses on the automation of these extraction techniques and subsequently, the integration of water sampling to give a totally automated analytical platform suitable for real-time monitoring of the environmental waters. This helps to provide insights on the future trend for sample preparation. | |
dc.language.iso | en | |
dc.subject | Sample preparation, Liquid-phase microextraction, Automation, Liquid chromatography-tandem mass spectrometry, Environmental analysis, Membranes | |
dc.type | Thesis | |
dc.contributor.department | CHEMISTRY | |
dc.contributor.supervisor | Hian Kee Lee | |
dc.description.degree | Ph.D | |
dc.description.degreeconferred | DOCTOR OF PHILOSOPHY (FOS) | |
Appears in Collections: | Ph.D Theses (Open) |
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GohXLS.pdf | 4.47 MB | Adobe PDF | OPEN | None | View/Download |
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