Enhanced zinc oxide and graphene nanostructures for electronics and sensing applications

Zinc oxide and graphene nanostructures are important technological materials because of their unique properties and potential applications in future generation of electronic and sensing devices. This dissertation investigates a brief account of the strategies to grow zinc oxide nanostructures (thin film and nanowire) and graphene, and their applications as enhanced field effect transistors, chemical sensors and transparent flexible electrodes. Nanostructured zinc oxide (ZnO) and low-gallium doped zinc oxide (GZO) thin films were synthesized by a magnetron sputtering process. Zinc oxide nanowires (ZNWs) were grown by a chemical vapor deposition method. Field effect transistors (FETs) of ZnO and GZO thin films and ZNWs were fabricated by standard photo and electron beam lithography processes. Electrical characteristics of these devices were investigated by nondestructive surface cleaning, ultraviolet irradiation treatment at high temperature and under vacuum. GZO thin film transistors showed a mobility of ∼5.7 cm2/V·s at low operation voltage of <5 V and a low turn-on voltage of ∼0.5 V with a sub threshold swing of ∼85 mV/decade. Bottom gated FET fabricated from ZNWs exhibit a very high on-to-off ratio (∼106) and mobility (∼28 cm2/V·s). A bottom gated FET showed large hysteresis of ∼5.0 to 8.0 V which was significantly reduced to ∼1.0 V by the surface treatment process. The results demonstrate charge transport in ZnO nanostructures strongly depends on its surface environmental conditions and can be explained by formation of depletion layer at the surface by various surface states. A nitric oxide (NO) gas sensor using single ZNW, functionalized with Cr nanoparticles was developed. The sensor exhibited average sensitivity of ∼46% and a minimum detection limit of ∼1.5 ppm for NO gas. The sensor also is selective towards NO gas as demonstrated by a cross sensitivity test with N2, CO and CO2 gases. Graphene film on copper foil was synthesized by chemical vapor deposition method. A hot press lamination process was developed for transferring graphene film to flexible polymer substrate. The graphene/polymer film exhibited a high quality, flexible transparent conductive structure with unique electrical-mechanical properties; ∼88.80% light transmittance and ∼1.1742Ω/sq k sheet resistance. The application of a graphene/polymer film as a flexible and transparent electrode for field emission displays was demonstrated.

A preliminary analysis of the correlation of food-web characteristics with hydrology and nutrient gradients in the southern Everglades

We estimated trophic position and carbon source for three consumers (Florida gar, Lepisosteus platyrhincus; eastern mosquitofish, Gambusia holbrooki; and riverine grass shrimp, Palaemonetes paludosus) from 20 sites representing gradients of productivity and hydrological disturbance in the southern Florida Everglades, U.S.A. We characterized gross primary productivity at each site using light/dark bottle incubation and stem density of emergent vascular plants. We also documented nutrient availability as total phosphorus (TP) in floc and periphyton, and the density of small fishes. Hydrological disturbance was characterized as the time since a site was last dried and the average number of days per year the sites were inundated for the previous 10 years. Food-web attributes were estimated in both the wet and dry seasons by analysis of δ15N (trophic position) and δ13C (food-web carbon source) from 702 samples of aquatic consumers. An index of carbon source was derived from a two-member mixing model with Seminole ramshorn snails (Planorbella duryi) as a basal grazing consumer and scuds (amphipods Hyallela azteca) as a basal detritivore. Snails yielded carbon isotopic values similar to green algae and diatoms, while carbon values of scuds were similar to bulk periphyton and floc; carbon isotopic values of cyanobacteria were enriched in C13compared to all consumers examined. A carbon source similar to scuds dominated at all but one study site, and though the relative contribution of scud-like and snail-like carbon sources was variable, there was no evidence that these contributions were a function of abiotic factors or season. Gar consistently displayed the highest estimated trophic position of the consumers studied, with mosquitofish feeding at a slightly lower level, and grass shrimp feeding at the lowest level. Trophic position was not correlated with any nutrient or productivity parameter, but did increase for grass shrimp and mosquitofish as the time following droughts increased. Trophic position of Florida gar was positively correlated with emergent plant stem density.

Cascade artificial neural networks technique for solving ellipsometry problems

Ellipsometry is a well known optical technique used for the characterization of reflective surfaces in study and films between two media. It is based on measuring the change in the state of polarization that occurs as a beam of polarized light is reflected from or transmitted through the film. Measuring this change can be used to calculate parameters of a single layer film such as the thickness and the refractive index. However, extracting these parameters of interest requires significant numerical processing due to the noninvertible equations. Typically, this is done using least squares solving methods which are slow and adversely affected by local minima in the solvable surface. This thesis describes the development and implementation of a new technique using only Artificial Neural Networks (ANN) to calculate thin film parameters. The new method offers a speed in the orders of magnitude faster than preceding methods and convergence to local minima is completely eliminated.