Responsive core-shell particles have attracted considerable attention over the last decade due to requirements imposed on materials to be more suited for their environment, with the provision to react accordingly when it changes. The responsive component in these cases is a polymer shell, with the core mostly introducing a static dimension, functioning as a structural support, and in some cases providing an indicator of stability. Generally, medium solvency is the key driving force for the behaviour of environmentally responsive polymer shells. To date, numerous novel techniques for the construction of these hybrid particles have been presented, and these can he classified according to the pre synthesis state of the core and shell materials. In addition to responsive behaviour, dimensional control and density of the shell layer being good indicators of a viable method, it is becoming equally important from a green chemistry perspective to minimize processing times and the use of harmful solvents. This thesis describes two main studies: a novel method for the rapid synthesis of environmentally responsive core-shell particles in an aqueous medium, and the responsive behaviour of morphologically similar particles at the air-water interface. The former study exploits the responsive character of the shell polymer to facilitate rapid adsorption onto a the surface of a colloidal dispersion while preventing aggregation. The resultant core-shell particles acquire the character of the polymer, and exhibit cyclic responsiveness. The latter study describes the adsorption behaviour of similar core-shell particles. By manipulating the medium solvency, the interfacial affinity of these particles is probed, and when combined with desorption kinetics and compression studies, reveals how these particles may function when used as foam stabilizers.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:614644 |
| Date | January 2012 |
| Creators | D'Souza-Mathew, Mark |
| Publisher | University of Leeds |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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