This thesis presents advances made to the scanning ion conductance microscope (SICM), a tool predominantly used to date for topographical imaging of biological samples. This technique is demonstrated to be a powerful tool for non-invasive surface charge mapping as well, through probing of the diffuse double layer formed at charged interfaces. Surface charge mapping with SICM is demonstrated for a range of samples, including biological systems, and it is shown that through the use of a novel feedback technique, also introduced herein, and newly implemented scanning regimes, that the surface charge information can be elucidated unambiguously, together with topography. Through adopting a characterisation protocol presented in this work, which helps provide a fuller understanding of the used nanopipette probe, the SICM response to charged interfaces and also in bulk solution can become quantitative, allowing for surface charge values for cell membranes and other substrates to be determined. This combination of: SICM experiments, complete probe characterisation and FEM simulations serves as a robust platform for investigating biological and other charged interfaces. The surface charge mapping protocols used allow for unseen surface charge heterogeneities, presented on cell membranes, to be identified and are amenable to future studies, performed in combination with other microscopy techniques, that could help correlate charged domains with physiological function. Finally, the nanopipette probe is also used as a reaction centre for driving the crystallisation of calcium carbonate, as an exemplar system. Through partitioning the constituent ions of calcium carbonate, with calcium present in a bath solution, and carbonate ions in a nanopipette, a bias can subsequently be applied to drive the ions together, leading to the formation of a crystalline entity, which blocks the nanopipette. Changes in the nanopipette conductance can then provide information about the growth process or subsequently the dissolution as the applied bias is reversed. FEM simulations can allow for an understanding of the underlying mixing problem and the technique is shown to be powerful for the screening of growth additives.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:714906 |
| Date | January 2016 |
| Creators | Perry, David |
| Publisher | University of Warwick |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://wrap.warwick.ac.uk/88301/ |
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