Many nonferrous industries such as mining and surface treatment plants produce co-products that are high in heavy metals and therefore toxic to the environment. A less obvious producer of heavy metal containing co-products is the whisky industry. Current methods of copper removal from such co-products include electrolysis and membrane filtration which are impractical and costly. When copper is found as a salt, current methods of removal include settlement, filtration and precipitation. Alternatives such as biological copper ion removal from effluents has also been shown to be effective. This study aimed to develop a biological method for the synthesis of stable copper nanoparticles. Morganella psychrotolerans was used to reduce Cu2+ to insoluble Cu0 nanoparticles. The nanoparticles were purified and characterised using X-Ray Photoelectron Spectroscopy (XPS) and High-Resolution Transmission Electron Microscopy (HR-TEM). Whisky distillery co-products were tested as a growth medium for M. psychrotolerans with concomitant copper nanoparticle synthesis. The copper nanoparticles were also studied for their application in electronics in order to make conductive circuits. Genomics studies combined with proteomics, helped develop possible models for copper nanoparticle synthesis by M. psychrotolerans, as well as identify proteins and genes not previously thought to be related to this pathway. The genome sequence of M. psychrotolerans obtained in this work allowed for a far more detailed study on the mechanism of copper nanoparticle synthesis than previously possible. This thesis also focused on understanding this mechanism better through proteomics and qRT-PCR. In order to study the identified copper ion reduction pathway in the future, a genetic modification toolkit was developed for M. psychrotolerans.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:739089 |
| Date | January 2017 |
| Creators | Pantidos, Nikolaos |
| Contributors | Horsfall, Louise ; Arnot, David |
| Publisher | University of Edinburgh |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1842/29532 |
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