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Metal hydride materials have been intensively studied for hydrogen storage applications. In addition to potential hydrogen economy applications, metal hydrides offer a wide variety of other interesting properties. For example, hydrogen-dominant materials, which are hydrides with the highest hydrogen content for a particular metal/semimetal composition, are predicted to display high-temperature

Metal hydride materials have been intensively studied for hydrogen storage applications. In addition to potential hydrogen economy applications, metal hydrides offer a wide variety of other interesting properties. For example, hydrogen-dominant materials, which are hydrides with the highest hydrogen content for a particular metal/semimetal composition, are predicted to display high-temperature superconductivity. On the other side of the spectrum are hydrides with small amounts of hydrogen (0.1 - 1 at.%) that are investigated as viable magnetic, thermoelectric or semiconducting materials. Research of metal hydride materials is generally important to gain fundamental understanding of metal-hydrogen interactions in materials. Hydrogenation of Zintl phases, which are defined as compounds between an active metal (alkali, alkaline earth, rare earth) and a p-block metal/semimetal, were attempted by a hot sintering method utilizing an autoclave loaded with gaseous hydrogen (< 9 MPa). Hydride formation competes with oxidative decomposition of a Zintl phase. The oxidative decomposition, which leads to a mixture of binary active metal hydride and p-block element, was observed for investigated aluminum (Al) and gallium (Ga) containing Zintl phases. However, a new phase Li2Al was discovered when Zintl phase precursors were synthesized. Using the single crystal x-ray diffraction (SCXRD), the Li2Al was found to crystallize in an orthorhombic unit cell (Cmcm) with the lattice parameters a = 4.6404(8) Å, b = 9.719(2) Å, and c = 4.4764(8) Å. Increased demand for materials with improved properties necessitates the exploration of alternative synthesis methods. Conventional metal hydride synthesis methods, like ball-milling and autoclave technique, are not responding to the demands of finding new materials. A viable alternative synthesis method is the application of high pressure for the preparation of hydrogen-dominant materials. Extreme pressures in the gigapascal ranges can open access to new metal hydrides with novel structures and properties, because of the drastically increased chemical potential of hydrogen. Pressures up to 10 GPa can be easily achieved using the multi-anvil (MA) hydrogenations while maintaining sufficient sample volume for structure and property characterization. Gigapascal MA hydrogenations using ammonia borane (BH3NH3) as an internal hydrogen source were employed in the search for new hydrogen-dominant materials. Ammonia borane has high gravimetric volume of hydrogen, and additionally the thermally activated decomposition at high pressures lead to a complete hydrogen release at reasonably low temperature. These properties make ammonia borane a desired hydrogen source material. The missing member Li2PtH6 of the series of A2PtH6 compounds (A = Na to Cs) was accessed by employing MA technique. As the known heavier analogs, the Li2PtH6 also crystallizes in a cubic K2PtCl6-type structure with a cell edge length of 6.7681(3) Å. Further gigapascal hydrogenations afforded the compounds K2SiH6 and Rb2SiH6 which are isostructural to Li2PtH6. The cubic K2SiH6 and Rb2SiH6 are built from unique hypervalent SiH62- entities with the lattice parameters of 7.8425(9) and 8.1572(4) Å, respectively. Spectroscopic analysis of hexasilicides confirmed the presence of hypervalent bonding. The Si-H stretching frequencies at 1550 cm-1 appeared considerably decreased in comparison with a normal-valent (2e2c) Si-H stretching frequencies in SiH4 at around 2200 cm-1. However, the observed stretching modes in hypervalent hexasilicides were in a reasonable agreement with Ph3SiH2- (1520 cm-1) where the hydrogen has the axial (3e4c bonded) position in the trigoal bipyramidal environment.
ContributorsPuhakainen, Kati (Author) / Häussermann, Ulrich (Thesis advisor) / Seo, Dong (Thesis advisor) / Kouvetakis, John (Committee member) / Wolf, George (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Sparsity has become an important modeling tool in areas such as genetics, signal and audio processing, medical image processing, etc. Via the penalization of l-1 norm based regularization, the structured sparse learning algorithms can produce highly accurate models while imposing various predefined structures on the data, such as feature groups

Sparsity has become an important modeling tool in areas such as genetics, signal and audio processing, medical image processing, etc. Via the penalization of l-1 norm based regularization, the structured sparse learning algorithms can produce highly accurate models while imposing various predefined structures on the data, such as feature groups or graphs. In this thesis, I first propose to solve a sparse learning model with a general group structure, where the predefined groups may overlap with each other. Then, I present three real world applications which can benefit from the group structured sparse learning technique. In the first application, I study the Alzheimer's Disease diagnosis problem using multi-modality neuroimaging data. In this dataset, not every subject has all data sources available, exhibiting an unique and challenging block-wise missing pattern. In the second application, I study the automatic annotation and retrieval of fruit-fly gene expression pattern images. Combined with the spatial information, sparse learning techniques can be used to construct effective representation of the expression images. In the third application, I present a new computational approach to annotate developmental stage for Drosophila embryos in the gene expression images. In addition, it provides a stage score that enables one to more finely annotate each embryo so that they are divided into early and late periods of development within standard stage demarcations. Stage scores help us to illuminate global gene activities and changes much better, and more refined stage annotations improve our ability to better interpret results when expression pattern matches are discovered between genes.
ContributorsYuan, Lei (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Xue, Guoliang (Committee member) / Kumar, Sudhir (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The rapid escalation of technology and the widespread emergence of modern technological equipments have resulted in the generation of humongous amounts of digital data (in the form of images, videos and text). This has expanded the possibility of solving real world problems using computational learning frameworks. However, while gathering a

The rapid escalation of technology and the widespread emergence of modern technological equipments have resulted in the generation of humongous amounts of digital data (in the form of images, videos and text). This has expanded the possibility of solving real world problems using computational learning frameworks. However, while gathering a large amount of data is cheap and easy, annotating them with class labels is an expensive process in terms of time, labor and human expertise. This has paved the way for research in the field of active learning. Such algorithms automatically select the salient and exemplar instances from large quantities of unlabeled data and are effective in reducing human labeling effort in inducing classification models. To utilize the possible presence of multiple labeling agents, there have been attempts towards a batch mode form of active learning, where a batch of data instances is selected simultaneously for manual annotation. This dissertation is aimed at the development of novel batch mode active learning algorithms to reduce manual effort in training classification models in real world multimedia pattern recognition applications. Four major contributions are proposed in this work: $(i)$ a framework for dynamic batch mode active learning, where the batch size and the specific data instances to be queried are selected adaptively through a single formulation, based on the complexity of the data stream in question, $(ii)$ a batch mode active learning strategy for fuzzy label classification problems, where there is an inherent imprecision and vagueness in the class label definitions, $(iii)$ batch mode active learning algorithms based on convex relaxations of an NP-hard integer quadratic programming (IQP) problem, with guaranteed bounds on the solution quality and $(iv)$ an active matrix completion algorithm and its application to solve several variants of the active learning problem (transductive active learning, multi-label active learning, active feature acquisition and active learning for regression). These contributions are validated on the face recognition and facial expression recognition problems (which are commonly encountered in real world applications like robotics, security and assistive technology for the blind and the visually impaired) and also on collaborative filtering applications like movie recommendation.
ContributorsChakraborty, Shayok (Author) / Panchanathan, Sethuraman (Thesis advisor) / Balasubramanian, Vineeth N. (Committee member) / Li, Baoxin (Committee member) / Mittelmann, Hans (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The increasing popularity of Twitter renders improved trustworthiness and relevance assessment of tweets much more important for search. However, given the limitations on the size of tweets, it is hard to extract measures for ranking from the tweet's content alone. I propose a method of ranking tweets by generating a

The increasing popularity of Twitter renders improved trustworthiness and relevance assessment of tweets much more important for search. However, given the limitations on the size of tweets, it is hard to extract measures for ranking from the tweet's content alone. I propose a method of ranking tweets by generating a reputation score for each tweet that is based not just on content, but also additional information from the Twitter ecosystem that consists of users, tweets, and the web pages that tweets link to. This information is obtained by modeling the Twitter ecosystem as a three-layer graph. The reputation score is used to power two novel methods of ranking tweets by propagating the reputation over an agreement graph based on tweets' content similarity. Additionally, I show how the agreement graph helps counter tweet spam. An evaluation of my method on 16~million tweets from the TREC 2011 Microblog Dataset shows that it doubles the precision over baseline Twitter Search and achieves higher precision than current state of the art method. I present a detailed internal empirical evaluation of RAProp in comparison to several alternative approaches proposed by me, as well as external evaluation in comparison to the current state of the art method.
ContributorsRavikumar, Srijith (Author) / Kambhampati, Subbarao (Thesis advisor) / Davulcu, Hasan (Committee member) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
One of the main challenges in planetary robotics is to traverse the shortest path through a set of waypoints. The shortest distance between any two waypoints is a direct linear traversal. Often times, there are physical restrictions that prevent a rover form traversing straight to a waypoint. Thus, knowledge of

One of the main challenges in planetary robotics is to traverse the shortest path through a set of waypoints. The shortest distance between any two waypoints is a direct linear traversal. Often times, there are physical restrictions that prevent a rover form traversing straight to a waypoint. Thus, knowledge of the terrain is needed prior to traversal. The Digital Terrain Model (DTM) provides information about the terrain along with waypoints for the rover to traverse. However, traversing a set of waypoints linearly is burdensome, as the rovers would constantly need to modify their orientation as they successively approach waypoints. Although there are various solutions to this problem, this research paper proposes the smooth traversability of the rover using splines as a quick and easy implementation to traverse a set of waypoints. In addition, a rover was used to compare the smoothness of the linear traversal along with the spline interpolations. The data collected illustrated that spline traversals had a less rate of change in the velocity over time, indicating that the rover performed smoother than with linear paths.
ContributorsKamasamudram, Anurag (Author) / Saripalli, Srikanth (Thesis advisor) / Fainekos, Georgios (Thesis advisor) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The ability to design high performance buildings has acquired great importance in recent years due to numerous federal, societal and environmental initiatives. However, this endeavor is much more demanding in terms of designer expertise and time. It requires a whole new level of synergy between automated performance prediction with the

The ability to design high performance buildings has acquired great importance in recent years due to numerous federal, societal and environmental initiatives. However, this endeavor is much more demanding in terms of designer expertise and time. It requires a whole new level of synergy between automated performance prediction with the human capabilities to perceive, evaluate and ultimately select a suitable solution. While performance prediction can be highly automated through the use of computers, performance evaluation cannot, unless it is with respect to a single criterion. The need to address multi-criteria requirements makes it more valuable for a designer to know the "latitude" or "degrees of freedom" he has in changing certain design variables while achieving preset criteria such as energy performance, life cycle cost, environmental impacts etc. This requirement can be met by a decision support framework based on near-optimal "satisficing" as opposed to purely optimal decision making techniques. Currently, such a comprehensive design framework is lacking, which is the basis for undertaking this research. The primary objective of this research is to facilitate a complementary relationship between designers and computers for Multi-Criterion Decision Making (MCDM) during high performance building design. It is based on the application of Monte Carlo approaches to create a database of solutions using deterministic whole building energy simulations, along with data mining methods to rank variable importance and reduce the multi-dimensionality of the problem. A novel interactive visualization approach is then proposed which uses regression based models to create dynamic interplays of how varying these important variables affect the multiple criteria, while providing a visual range or band of variation of the different design parameters. The MCDM process has been incorporated into an alternative methodology for high performance building design referred to as Visual Analytics based Decision Support Methodology [VADSM]. VADSM is envisioned to be most useful during the conceptual and early design performance modeling stages by providing a set of potential solutions that can be analyzed further for final design selection. The proposed methodology can be used for new building design synthesis as well as evaluation of retrofits and operational deficiencies in existing buildings.
ContributorsDutta, Ranojoy (Author) / Reddy, T Agami (Thesis advisor) / Runger, George C. (Committee member) / Addison, Marlin S. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Continuous Delivery, as one of the youngest and most popular member of agile model family, has become a popular concept and method in software development industry recently. Instead of the traditional software development method, which requirements and solutions must be fixed before starting software developing, it promotes adaptive planning, evolutionary

Continuous Delivery, as one of the youngest and most popular member of agile model family, has become a popular concept and method in software development industry recently. Instead of the traditional software development method, which requirements and solutions must be fixed before starting software developing, it promotes adaptive planning, evolutionary development and delivery, and encourages rapid and flexible response to change. However, several problems prevent Continuous Delivery to be introduced into education world. Taking into the consideration of the barriers, we propose a new Cloud based Continuous Delivery Software Developing System. This system is designed to fully utilize the whole life circle of software developing according to Continuous Delivery concepts in a virtualized environment in Vlab platform.
ContributorsDeng, Yuli (Author) / Huang, Dijiang (Thesis advisor) / Davulcu, Hasan (Committee member) / Chen, Yinong (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Topological insulators with conducting surface states yet insulating bulk states have generated a lot of interest amongst the physics community due to their varied characteristics and possible applications. Doped topological insulators have presented newer physical states of matter where topological order co&ndashexists; with other physical properties (like magnetic order). The

Topological insulators with conducting surface states yet insulating bulk states have generated a lot of interest amongst the physics community due to their varied characteristics and possible applications. Doped topological insulators have presented newer physical states of matter where topological order co&ndashexists; with other physical properties (like magnetic order). The electronic states of these materials are very intriguing and pose problems and the possible solutions to understanding their unique behaviors. In this work, we use Electron Energy Loss Spectroscopy (EELS) – an analytical TEM tool to study both core&ndashlevel; and valence&ndashlevel; excitations in Bi2Se3 and Cu(doped)Bi2Se3 topological insulators. We use this technique to retrieve information on the valence, bonding nature, co-ordination and lattice site occupancy of the undoped and the doped systems. Using the reference materials Cu(I)Se and Cu(II)Se we try to compare and understand the nature of doping that copper assumes in the lattice. And lastly we utilize the state of the art monochromated Nion UltraSTEM 100 to study electronic/vibrational excitations at a record energy resolution from sub-nm regions in the sample.
ContributorsSubramanian, Ganesh (Author) / Spence, John (Thesis advisor) / Jiang, Nan (Committee member) / Chen, Tingyong (Committee member) / Chan, Candace (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Microelectronic industry is continuously moving in a trend requiring smaller and smaller devices and reduced form factors with time, resulting in new challenges. Reduction in device and interconnect solder bump sizes has led to increased current density in these small solders. Higher level of electromigration occurring due to increased current

Microelectronic industry is continuously moving in a trend requiring smaller and smaller devices and reduced form factors with time, resulting in new challenges. Reduction in device and interconnect solder bump sizes has led to increased current density in these small solders. Higher level of electromigration occurring due to increased current density is of great concern affecting the reliability of the entire microelectronics systems. This paper reviews electromigration in Pb- free solders, focusing specifically on Sn0.7wt.% Cu solder joints. Effect of texture, grain orientation, and grain-boundary misorientation angle on electromigration and intermetallic compound (IMC) formation is studied through EBSD analysis performed on actual C4 bumps.
ContributorsLara, Leticia (Author) / Tasooji, Amaneh (Thesis advisor) / Lee, Kyuoh (Committee member) / Krause, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Magnetic Resonance Imaging using spiral trajectories has many advantages in speed, efficiency in data-acquistion and robustness to motion and flow related artifacts. The increase in sampling speed, however, requires high performance of the gradient system. Hardware inaccuracies from system delays and eddy currents can cause spatial and temporal distortions in

Magnetic Resonance Imaging using spiral trajectories has many advantages in speed, efficiency in data-acquistion and robustness to motion and flow related artifacts. The increase in sampling speed, however, requires high performance of the gradient system. Hardware inaccuracies from system delays and eddy currents can cause spatial and temporal distortions in the encoding gradient waveforms. This causes sampling discrepancies between the actual and the ideal k-space trajectory. Reconstruction assuming an ideal trajectory can result in shading and blurring artifacts in spiral images. Current methods to estimate such hardware errors require many modifications to the pulse sequence, phantom measurements or specialized hardware. This work presents a new method to estimate time-varying system delays for spiral-based trajectories. It requires a minor modification of a conventional stack-of-spirals sequence and analyzes data collected on three orthogonal cylinders. The method is fast, robust to off-resonance effects, requires no phantom measurements or specialized hardware and estimate variable system delays for the three gradient channels over the data-sampling period. The initial results are presented for acquired phantom and in-vivo data, which show a substantial reduction in the artifacts and improvement in the image quality.
ContributorsBhavsar, Payal (Author) / Pipe, James G (Thesis advisor) / Frakes, David (Committee member) / Kodibagkar, Vikram (Committee member) / Arizona State University (Publisher)
Created2013