The concepts of electroneutrality coupling and electron-hopping, which are useful for the incorporation of functional components and transportation of electrons, were applied in this project. Discrete layered structures were fabricated by sequential electropolymerization to modulate the performances of formate biosensors. Different types of layers, with or without enzyme, were successfully grown on the electrode surface. The presence of the enzyme (formate dehydrogenase), co-factor (B-nicotinamide adenine dinucleotide) and an electron mediator in the polypyrrole film was verified by scanning electron microscopy, chronopotentiometry, cyclic voltammetry and amperometric measurements. Monolayer, bilayer and trilayer formate biosensors were successfully fabricated for different analytical purposes. The utilisation of the biosensing membrane for the reliable batch and FIA determination of formate based on a amperometric mode of detection are explored. Electron mediators such as ferrocyanide, Prussian Blue, ferrocene and ferrocene carboxylic acid were incorporated into the polypyrrole film to lower the required applied potential for amperometric sensing and to maintain the conductivity and stability of the polypyrrole backbone. The application of artificial neural networks (ANN) to overcome the problem of reusability and reproducibilty in a nonlinear and complicated dynamic system is also considered. The resulting system was trained with a new neural network based software package, Turbo Neuron, for prediction of the concentration of formate, based on the entire collected data, which contain the history of the detection experiments. The proposed integrated ANN conducting polymer biosensor enables the determination of formate concentration, both online and in real time / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:ADTP/234890 |
| Date | January 1998 |
| Creators | Yuan, Yong J., University of Western Sydney, School of Civic Engineering and Environment |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Source | THESIS_XXXX_CEE_Yuan_Y.xml |
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