Graphene is a novel material that has exceptional electrical properties. In this work the graphene-based devices were developed towards three applications. Graphene-glass electrodes were fabricated and characterised towards understanding the electrochemical nature of graphene. It was shown that graphene could serve as an electrochemical electrode towards use as a sensing platform due to its fast electron transfer characteristics and thus exhibited potential as a platform for electrochemical sensing of electroactive species. Further, the Graphene-on-Glass electrodes were shown to be used as a working electrode to create a reversible electrochromic device where the optical transparency of the Graphene was modulated, and the electrochemical characteristics of the Graphene device were examined. A proof-of-concept detection for the presence of a biomarker for Sepsis was developed. Large-area, functionalised graphene was shown to able to electronically sense the presence of the binding events of the Anti-PCT antibody, PCT molecule and differentiate from their bulk solution. The device was able to detect the presence of PCT over the medically relevant range. This sensor combines the exceptional electrical properties of graphene leading to high sensitivity, which when functionalized also yields high specificity as a sensor platform and offers a new route for diagnosis of Sepsis electronically in real time measurements. Lastly, a hybrid graphene FET array that is embedded under microfluidic channels was developed. The effect of water on the device was measured and the utility of such devices towards sensing in aqueous media is discussed. Further, it is shown that the microfluidic channels of varying widths are able to transport water along the graphene FET array, such that individual graphene strips can sense them. This measurement scheme is extremely useful and can be adapted to a host of other sensing applications which would benefit from dynamic and precise control on the detection of the analyte.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:761799 |
| Date | January 2018 |
| Creators | Eashwer Singhraj, Sneha |
| Contributors | Horsell, David |
| Publisher | University of Exeter |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10871/34651 |
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