In order to better understand the fundamental components that govern catalytic activity, two-dimensional model platinum nanocatalyst arrays have been designed and fabricated. These catalysts arrays are meant to model the interplay of the metal and support important to industrial heterogeneous catalytic reactions. Photolithography and sub-lithographic techniques such as electron beam lithography, size reduction lithography and nanoimprint lithography have been employed to create these platinum nanoarrays. Both in-situ and ex-situ surface science techniques and catalytic reaction measurements were used to correlate the structural parameters of the system to catalytic activity.

We are becoming dependent on energy more today than we were a century ago, and with increasing world population and booming economies, sooner or later our energy sources will be exhausted. Moreover, our economy and welfare strongly depends on foreign oil and in the shadow of political uncertainties, there is an urgent need for a reliable, safe, and cheap energy source. Thermonuclear fusion, if achieved, is that source of energy which not only will satisfy our demand for today but also for centuries to come. Today, there are two major approaches to achieve fusion: magnetic confinement fusion (MFE) and inertial confinement fusion (ICF). This dissertation explores the inertial confinement fusion using the fast ignition concept. Unlike the conventional approach where the same laser is used for compression and ignition, in fast ignition separate laser beams are used. This dissertation addresses three very important topics to fast ignition inertial confinement fusion. These are laser-to-electron coupling efficiency, laser-generated electron beam transport, and the associated isochoric heating. First, an integrated fast ignition experiment is carried out with 0.9 kJ of energy in the compression beam and 70 J in the ignition beam. Measurements of absolute K{sub {alpha}} yield from the imploded core revealed …

The castor bean plant (Ricinus communis) is a member of the family Euphorbiaceae. In spite of its common name, the castor plant is not a true bean (i.e., leguminous plants belonging to the family, Fabaceae). Ricinus communis is native to tropical Africa, but because the plant was recognized for its production of oil with many desirable properties, it has been introduced and cultivated in warm temperate regions throughout the world (Armstrong 1999 and Brown 2005). Castor bean plants have also been valued by gardeners as an ornamental plant and, historically, as a natural rodenticide. Today, escaped plants grow like weeds throughout much of the southwestern United States, and castor seeds are even widely available to the public for order through the Internet. In this study, multiple loci of chloroplast noncoding sequence data and a few nuclear noncoding regions were examined to identify DNA polymorphisms present among representatives from a geographically diverse panel of Ricinus communis cultivated varieties. The primary objectives for this research were (1) to successfully cultivate castor plants and extract sufficient yields of high quality DNA from an assortment of castor cultivated varieties, (2) to use PCR and sequencing to screen available universal oligos against a small panel …

Much of the previous work in the large data visualization area has solely focused on handling the scale of the data. This task is clearly a great challenge and necessary, but it is not sufficient. Applying standard visualization techniques to large scale data sets often creates complicated pictures where meaningful trends are lost. A second challenge, then, is to also provide algorithms that simplify what an analyst must understand, using either visual or quantitative means. This challenge can be summarized as improving the legibility or reducing the complexity of massive data sets. Fully meeting both of these challenges is the work of many, many PhD dissertations. In this dissertation, we describe some new techniques to address both the scale and legibility challenges, in hope of contributing to the larger solution. In addition to our assumption of simultaneously addressing both scale and legibility, we add an additional requirement that the solutions considered fit well within an interoperable framework for diverse algorithms, because a large suite of algorithms is often necessary to fully understand complex data sets. For scale, we present a general architecture for handling large data, as well as details of a contract-based system for integrating advanced optimizations into a …