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Zinc oxide (ZnO) is a metal-oxide semiconductor with a direct wide band gap and high exciton binding energy at room temperature. It has been applied to many applications such as solar cells, light emitting diodes, nano-generators and chemical sensors. In this thesis, a solution phase synthesis method has been used to produce ZnO nanorods on conductive substrates at low cost. By controlling the growth conditions, ZnO nanorods with an aspect ratio of 51 in a single step was achieved. The morphology, crystallisation, optical properties, band structures and carrier lifetime were analysed. Chemical sensors such as gas sensors play a very important role in our life and in industry. ZnO nanorods have been investigated as a sensing material to detect harmful gases such as NO2 and NH3. However, such a traditional sensing platform only works at high operating temperatures, which limits its application to portable devices or wireless devices. In order to decrease the working temperature, a Schottky diode was assembled by evaporating a gold layer on the top of the ZnO nanorods. Gas sensing results showed that this diode had good responses to NH3 gas at room temperature. It also displayed high selectivity to NH3 over acetone, CO2, CO and ethanol. Long-term tests demonstrated good stability over 7-weeks. ZnO nanorods are also a suitable sensing material for light-addressable potentiometric sensors (LAPS) that are designed to detect pH, redox ions and characterise cells and tissue. In contrast to the traditional electrolyte-insulator-semiconductor (EIS) structures, ZnO nanorods without an insulator were applied in LAPS and showed a spatial resolution of 3 μm. LAPS based on ZnO nanorods were used as a disposable biosensor for the detection of α-chymotrypsin. The effect of the ZnO morphology on the spatial resolution was also investigated.

Dendritic polymers have recently been shown to entrap polycyclic aromatic hydrocarbons (PAHs) and other hydrophobic materials. Laboratory results have shown that poly(amidoamine) dendrimers and hyperbranched poly(ethyleneimine) polymers form complexes with linear (hexadecane) and polyaromatic (phenanthrene) hydrocarbons, increasing the dispersion of these model crude oil components. It is thus hypothesized that crude oil can be dispersed using these polymers. Compared with commercial dispersants, dendritic polymers have the potential to be more biocompatible and less toxic. The objective of this research was to gain a fundamental understanding of the interactions of dendritic polymers with crude oil. We used Louisians Sweet Crude oil to explore the dispersion effectiveness of the polymers and the mechanisms of oil-polymer interactions. Results were compared with Corexit 9500, the dispersant used in response to the Deepwater Horizon disaster of 2010. We investigated the factors that may influence the experimental results, such as dispersant to oil ratio (DOR), mixing and settling time, sample preparation methods and sample collection methods to establish experimental protocols that adequately characterized the effectiveness of the polymers. The effects of polymer size and surface groups on oil dispersion effectiveness were examined through an optimized effectiveness test. Five hyperbranched polyethylenimine polymers (HY-PEI) with molecular weight 1.2, 1.8, 10, 70 and 750 kDa and amino surface terminal groups were examined with the effectiveness test. The results showed the 10 kDa HY-PEI had the highest dispersion efficiency (58%) slightly larger than Corexit (56%). 70 kDa and 750 kDa HY-PEI also had a relatively high effectiveness, 48% and 40% respectively; however, the low molecular weight polymers, 1.2 kDa and 1.8 kDa had low dispersion efficiency, 11% and 17%, similar to the no dispersant scenario which had 13% oil dispersion. We also tested three dendrimers with different surface terminal groups: amino (positive charge), amidoethanol (neutral charge) and succinamic acid (negative charge). The results showed that G4-PAMAM-NH2 with positive surface charge had the highest efficiency of these three, 42%. G4-PAMAM-OH and G4-PAMAM-SA had lower dispersion capacity, with effectiveness of 16% and 19%. We concluded that the polymers with moderate size and positive charged surface groups are very capable in dispersing light sweet crude oil. Further exploring the interactions of dendritic polymers with crude oil, we conducted dynamic interfacial tension test and oil droplet size distribution test. The dynamic interfacial tension curves shows that all the polymers can reduce the interfacial tension and the larger polymers are more capable at decreasing the interfacial tension rapidly. The efficiency of polymer dispersion for oil has also been verified by drop size distribution measurements. Polymers with high performance in effectiveness test tend to create smaller droplets than polymers that show less effectiveness. Again, moderately sized polymers gave the smaller average droplet size and polydispersity. By further analyzing the data we developed a conceptual model for the oil dendritic polymer interaction, which is a hybrid surfactant and Pickering emulsion mechanism.

Information visualization, a field that studies visual representations of abstract data where no spatial representation is available, has been playing an essential role in assisting people to understand the vast amount of information created by modern technology. Visualizing large complex structured data is an important area as the structured data are ubiquitous in many aspects of our lives. The large size, high complexity, and vast variety in user interests pose formidable challenges to create effective representations for those structured data.To help users understand detailed information in the large dataset based on their changing interests, several focus-based interactive visualization methods have been described. To allow users to discover specific contextual information around the focus in large semantic graphs, we propose to use the embedded semantic queries during browsing as the main method for information discovery. In addition, to let users quickly understand the different aspects of the graph data, we propose to set up multiple contexts and enable users to quickly switch among the contexts without any abrupt layout changes. Moreover, to assist users in quickly identifying the focal entities when comparing two treemaps, we propose novel contrast techniques to highlight the key differences of the two treemaps in the context of a single treemap so that direct comparison can be done easily. Furthermore, to facilitate the study of the details of multiple foci in a treemap, we propose a focus+context technique to seamlessly enlarge multiple foci in the same view while maintaining a consistent and stable layout. The effectiveness of these approaches are evaluated by case studies and user studies, where we have clearly demonstrated that users can better understand the structured data with more details and in less amount of time. Both free exploration and task-oriented scenarios were studied in our experiments.