This thesis investigates the development of a vapour sensor that is useful in fields such as environmental protection, or healthcare. A summary review of vapour sensing techniques is given, leading to the choice of exploiting a simple, low cost, high-resolution mass sensing technique-Quartz Crystal Microbalance (QCM) to fabricate a lipid based vapour sensor. Both hydrophilic and hydrophobic vapours have been introduced in the sensing experiment. Three types of lipids based sensors, which were 1, 2-dilauroyl-sn-glycero-3-phosphocholine (DLPC), 1, 2-dioctadecanoyl-sn-glycero-3-phosphocholine (DSPC), cholesterol and their mixtures, were fabricated on AT cut quartz crystal based substrates by spin coating. Atomic Force Microscopy (AFM) was used for topography analysis; QCM was used for quantitative analysis. Film thickness data suggests that a bilayer DLPC is 4.3 nm and a bilayer DSPC is 5.8 nm thick. The average film thickness is approximately proportional to the coating concentration with a constant of proportionality of 4.3 nm/mM and 5.8 nm/mM for DLPC and DSPC, respectively. The results from the AFM and QCM trials have led to the development of a controllable process for the fabrication of a repeatable amount of lipid membrane based vapour sensors. The response of each film when exposed to ethanol, methanol, toluene and cyclohexane vapours was recorded. The results show that hydrophilic compounds could be recognised efficiently by lipids having shorter alkyl chains. Frequency changes caused by adsorption of test vapours could be enhanced when cholesterol was co-immobilised in the lipid layer. The best sensing behaviour (that is, excellent response, reversibility and negligible baseline drift) and sensitivity was achieved in a sensor coated with DLPC/DSPC/cholesterol mixed film (50 mg/ml DLPC/DSPC/cholesterol-1:1:8 in volume ratio). The limit of detection of this sensor is 400 ppm to ethanol, 800 ppm to methanol, 1300 ppm to toluene and 2300 ppm to cyclohexane, separately.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:620786 |
| Date | January 2014 |
| Creators | Duan, Xiao Xia |
| Publisher | Durham University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.dur.ac.uk/10738/ |
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