Aliovalent Dopants In Zno Nanocrystals: Synthesis To Electronic Structure, Dongming Zhou

Doctoral Dissertations

Semiconductor nanocrystal doping has stimulated broad interest for many applications including solar energy conversion, nanospintronics, and phosphors or optical labels. The study of the chemistry and physics of doped colloidal semiconductor nanocrystals has been dominated in the literature by isovalent dopants such as Mn²⁺ and Co²⁺ ions in II-VI semiconductors, in which the dopant oxidation state is the same as the cation ions. Until recently, aliovalent dopants has received much attention due to the plasmonic properties. Aliovalent is when the oxidation states of the dopant in the lattice differs from the cation ions. In the plasmonic semiconductor nanocrystals, …

Characterization Of Highly Heterogeneous Heparin-Protein Complexes Using Novel Mass Spectrometry-Based Approaches, Yunlong Zhao

Doctoral Dissertations

Heparin-like glycosaminoglycan (GAG) is a family of polysaccharide involved in variety of physiological processes. They have potentials to interact with a broad range of proteins and many of them hold crucial values in regulation of protein functions. My dissertation addresses the significance and challenges in the field of heparin-mediated studies, with a focus on the questions in biological and analytical aspects, which are largely hindered by the structural heterogeneity and function diversity of heparin. My dissertation reports the efforts I made in the past few years with respect to the development of novel analytical strategies based on a combination of …

Nanoparticle As Supramolecular Platform For Delivery And Bioorthogonal Catalysis, Gulen Yesilbag Tonga

Doctoral Dissertations

Nanoparticles (NPs) are being investigated widely for many applications including imaging, drug delivery, therapeutics, materials, and catalysis due to their unique and tunable physical and chemical properties. Among NPs, gold nanoparticles (AuNPs) have attracted great attention due to ease of synthesis and surface functionalization, inertness of the core, biocompatibility, and functional versatility. Introducing supramolecular chemistry into the nanoparticle-based platforms brings out controllable properties, dynamic self assembly processes, and adjustable performance. My research has focused on the synthesis of AuNPs bearing different surface functionalities and their host-guest interactions with synthetic small molecules or commercially available hydrophobic catalysts for delivery and therapeutic …

Assembly Of Particles Onto Rigid Cylinders And Flexible Membranes: Probing Effects Of Surface Curvature And Deformation, Derek Wood

Doctoral Dissertations

In this thesis we explore two specific topics within the broad field of particle adhesion. First, we examine the effect of substrate shape and geometry on the self assembly of adsorbed particles, by performing molecular dynamics simulations of interacting particles constrained to the surface of cylinders of varying diameters. We find the diameter of the cylinder imposes a constraint on the shape and crystallographic orientation of the self-assembled lattice, essentially determining the optimal arrangement of particles a priori. We propose a simple one-dimensional model to explain the optimal arrangement of particles as a function of the particle interaction potential …

A Categorical Formulation Of Algebraic Geometry, Bradley Willocks

Doctoral Dissertations

We construct a category, $\Omega$, of which the objects are pointed categories and the arrows are pointed correspondences. The notion of a ``spec datum" is introduced, as a certain relation between categories, of which one has been given a Grothendieck topology. A ``geometry" is interpreted as a sub-category of $\Omega$, and a formalism is given by which such a subcategory is to be associated to a spec datum, reflecting the standard construction of the category of schemes from the category of rings by affine charts.

Computational Studies Of Structure–Function Relationships Of Supported And Unsupported Metal Nanoclusters, Hongbo Shi

Doctoral Dissertations

Fuel cells have been demonstrated to be promising power generation devices to address the current global energy and environmental challenges. One of the many barriers to commercialization is the cost of precious catalysts needed to achieve sufficient power output. Platinum-based materials play an important role as electrocatalysts in energy conversion technologies. In order to improve catalytic efficiency and facilitate rational design and development of new catalysts, structure–function relationships that underpin catalytic activity must be understood at a fundamental level. First, we present a systematic analysis of CO adsorption on Pt nanoclusters in the 0.2-1.5 nm size range with the aim …

Analyses Of Densely Crosslinked Phenolic Systems Using Low Field Nmr, Jigneshkumar Patel

Doctoral Dissertations

A uniform dispersion of reactants is necessary to achieve a complete reaction involving multi-components, especially for the crosslinking of rigid high-performance materials. In these reactions, miscibility is crucial for curing efficiency. This miscibility is typically enhanced by adding a third component, a plasticizer. For the reaction of the highly crystalline crosslinking agent hexamethylenetetramine (HMTA) with a strongly hydrogen-bonded phenol formaldehyde resin, furfural has been traditionally used as the plasticizer. However, the reason for its effectiveness is not clear. In this doctoral thesis work, miscibility and crosslinking efficiency of plasticizers in phenolic curing reactions are studied by thermal analysis and spectroscopic …

Knowledge Representation And Reasoning With Deep Neural Networks, Arvind Ramanathan Neelakantan

Doctoral Dissertations

Knowledge representation and reasoning is one of the central challenges of artificial intelligence, and has important implications in many fields including natural language understanding and robotics. Representing knowledge with symbols, and reasoning via search and logic has been the dominant paradigm for many decades. In this work, we use deep neural networks to learn to both represent symbols and perform reasoning end-to-end from data. By learning powerful non-linear models, our approach generalizes to massive amounts of knowledge and works well with messy real-world data using minimal human effort. First, we show that recurrent neural networks with an attention mechanism achieve …

Protein-Nanoparticle Co-Engineering: Self-Assembly, Intracellular Protein Delivery, And Crispr/Cas9-Based Gene Editing, Rubul Mout

Doctoral Dissertations

Direct cytoplasmic delivery of gene editing nucleases such CRISPR/Cas9 systems and therapeutic proteins provides enormous opportunities in curing human genetic diseases, and assist research in basic cell biology. One approach to attain such a goal is through engineering nanotechnological tools to mimic naturally existing intra- and extracellular protein delivery/transport systems. Nature builds transport systems for proteins and other biomolecules through evolution-derived sophisticated molecular engineering. Inspired by such natural assemblies, I employed molecular engineering approaches to fabricate self-assembled nanostructures to use as intracellular protein delivery tools. Briefly, proteins and gold nanoparticles were co-engineered to carry complementary electrostatic recognition elements. When these …

Temporal And Relational Models For Causality: Representation And Learning, Katerina Marazopoulou

Doctoral Dissertations

Discovering causal dependence is central to understanding the behavior of complex systems and to selecting actions that will achieve particular outcomes. The majority of work in this area has focused on propositional domains, where data instances are assumed to be independent and identically distributed (i.i.d.). However, many real-world domains are inherently relational, i.e., they consist of multiple types of entities that interact with each other, and temporal, i.e., they change over time. This thesis focuses on causal modeling for these more complex relational and temporal domains. This thesis provides an in-depth investigation of the properties of relational models and is …

Conducting Polyelectrolyte Complexes: Assembly, Structure, And Transport, Michael A. Leaf

Doctoral Dissertations

Decades of progress have yielded a tremendous variety of organic electronics, with great strides in the development of photovoltaics, thermoelectrics and other flexible devices. Ubiquitous in these research areas are films of poly(3,4-ethylenedioxythiophene): poly(styrenesulfonic acid) (PEDOT: PSS), a complex of oppositely-charged polyelectrolytes initially suspended in water before film formation. This material has high electronic conductivity and good water processability. Pristine film conductivity is somewhat low, but is dramatically enhanced through simple treatments like ionic liquid addition or shear. Can this enhancement be understood so that further optimization might render PEDOT: PSS commercially viable? PEDOT: PSS is a complicated material, with …

Equations For Nilpotent Varieties And Their Intersections With Slodowy Slices, Benjamin Johnson

Doctoral Dissertations

This thesis investigates minimal generating sets of ideals defining certain nilpotent varieties in simple complex Lie algebras. A minimal generating set of invariants for the whole nilpotent cone is known due to Kostant. Broer determined a minimal generating set for the subregular nilpotent variety in all simple Lie algebra types. I extend Broer's results to two families of nilpotent varieties, valid in any simple Lie algebra, that include the nilpotent cone, the subregular case, and usually more. In the first part of my thesis I describe a minimal generating set for the ideal of each of these varieties in the …

Deep-Learned Generative Representations Of 3d Shape Families, Haibin Huang

Doctoral Dissertations

Digital representations of 3D shapes are becoming increasingly useful in several emerging applications, such as 3D printing, virtual reality and augmented reality. However, traditional modeling softwares require users to have extensive modeling experience, artistic skills and training to handle their complex interfaces and perform the necessary low-level geometric manipulation commands. Thus, there is an emerging need for computer algorithms that help novice and casual users to quickly and easily generate 3D content. In this work, I will present deep learning algorithms that are capable of automatically inferring parametric representations of shape families, which can be used to generate new 3D …

Production Of Cosmological Observables During The Inflationary Epoch, Cody Goolsby-Cole

Doctoral Dissertations

This dissertation proposal explores the production of present day cosmological observables which might have been produced during the inflationary era. The first observable is the current net electric charge of our observable universe produced by charge fluctuations during inflation. Next, we examine the possibility of a signal in the primordial gravitational wave power spectrum produced by a scalar field with a time dependent mass. Finally, we examine primordial magnetic fields produced during inflation through the Ratra model coupling with the Schwinger effect.

Coverings Of Graphs And Tiered Trees, Sam Glennon

Doctoral Dissertations

This dissertation will cover two separate topics. The first of these topics will be coverings of graphs. We will discuss a recent paper by Marcus, Spielman, and Srivastava proving the existence of infinite families of bipartite Ramanujan graphs for all regularities. The proof works by showing that for any d-regular Ramanujan graph, there exists an infinite tower of bipartite Ramanujan graphs in which each graph is a twofold covering of the previous one. Since twofold coverings of a graph correspond to ways of labeling the edges of the graph with elements of a group of order 2, we will generalize …

Database Usability Enhancement In Data Exploration, Yue Wang

Doctoral Dissertations

Database usability has become an important research topic over the last decade. In the early days, database management systems were maintained by sophisticated users like database administrators. Today, due to the availability of data and computing resources, more non-expert users are involved in database computation. From their point of view, database systems lack ease of use. So researchers believe that usability is as important as the performance and functionality of databases and therefore developed many techniques such as natural language interface to enhance the ease of use of databases. In this thesis, we find some deeper technical issues in database …

Adaft: A Resource-Efficient Framework For Adaptive Fault-Tolerance In Cyber-Physical Systems, Ye Xu

Doctoral Dissertations

Cyber-physical systems frequently have to use massive redundancy to meet application requirements for high reliability. While such redundancy is required, it can be activated adaptively, based on the current state of the controlled plant. Most of the time the physical plant is in a state that allows for a lower level of fault-tolerance. Avoiding the continuous deployment of massive fault-tolerance will greatly reduce the workload of CPSs. In this dissertation, we demonstrate a software simulation framework (AdaFT) that can automatically generate the sub-spaces within which our adaptive fault-tolerance can be applied. We also show the theoretical benefits of AdaFT, and …

Controversy Analysis And Detection, Shiri Dori-Hacohen

Doctoral Dissertations

Seeking information on a controversial topic is often a complex task. Alerting users about controversial search results can encourage critical literacy, promote healthy civic discourse and counteract the "filter bubble" effect, and therefore would be a useful feature in a search engine or browser extension. Additionally, presenting information to the user about the different stances or sides of the debate can help her navigate the landscape of search results beyond a simple "list of 10 links". This thesis has made strides in the emerging niche of controversy detection and analysis. The body of work in this thesis revolves around two …

The Complexity Of Resilience, Cibele Matos Freire

Doctoral Dissertations

One focus area in data management research is to understand how changes in the data can affect the output of a view or standing query. Example applications are explaining query results and propagating updates through views. In this thesis we study the complexity of the Resilience problem, which is the problem of finding the minimum number of tuples that need to be deleted from the database in order to change the result of a query. We will see that resilience is closely related to the well-studied problems of deletion propagation and causal responsibility, and that analyzing its complexity offers important …

Polyorganosiloxanes: Molecular Nanoparticles, Nanocomposites And Interfaces, Daniel H. Flagg

Doctoral Dissertations

Five research projects described. First, a reproducible, lab-scale synthesis of MQ silicone copolymers is presented. MQ copolymers are commercially important materials that have been ignored by the academic community. One possible reason for this is the difficulty of controlling and reproducing the preparative copolymerizations that have been reported. A reproducible method for lab-scale preparation was developed that controls molecular weight by splitting the copolymerization into the discrete steps of sol growth from silicate precursor and end-capping by trimethylsiloxy groups. Characterization of MQ products implicates that they are composed of highly condensed, polycyclic structures. The MQ copolymers prepared in the first …

Spectroscopic Studies Of Gas-Phase Transition Metal Complexes Of Cations And Cluster Ions With Methane And Water, Christopher Copeland

Doctoral Dissertations

The study of the non-covalent interactions between metals ions and ligands such as water and methane are key to understanding many processes including solvation, homogeneous catalysis and metals in biology. Similarly, the study of interactions between transition metal ions and cluster ions with hydrocarbons is of great importance in the understanding of C-H activation reactions which are involved in generation of fuels. Gas-phase metal complexes are good models for understanding the intrinsic interactions between the metal and the ligand. Understanding the mechanisms behind these interactions can be done by characterizing the structure and bonding in the molecular reactants, products, and …

Style-Driven Shape Analysis And Synthesis, Zhaoliang Lun

Doctoral Dissertations

In this dissertation I will investigate algorithms that analyze stylistic properties of 3D shapes and automatically synthesize shapes given style specifications. I will start by introducing a structure-transcending method for style similarity evaluation between 3D shapes. Inspired by observations about style similarity in art history literature, we propose an algorithmically computed style similarity measure which identifies style related elements on the analyzed models and collates element-level geometric similarity measurements into an object-level style measure consistent with human perception. To achieve this consistency we employ crowdsourcing to learn the relative perceptual importance of a range of elementary shape distances and other …

Graph Construction For Manifold Discovery, Cj Carey

Doctoral Dissertations

Manifold learning is a class of machine learning methods that exploits the observation that high-dimensional data tend to lie on a smooth lower-dimensional manifold. Manifold discovery is the essential first component of manifold learning methods, in which the manifold structure is inferred from available data. This task is typically posed as a graph construction problem: selecting a set of vertices and edges that most closely approximates the true underlying manifold. The quality of this learned graph is critical to the overall accuracy of the manifold learning method. Thus, it is essential to develop accurate, efficient, and reliable algorithms for constructing …

Environmentally Driven Galaxy Evolution And Quenching: Insights From The Low-Redshift Circumgalactic Medium, Joseph Burchett

Doctoral Dissertations

The gaseous halos of galaxies -- the circumgalactic medium (CGM) -- serve as interfaces playing host to the fueling and feedback processes that sustain and regulate star formation. Furthermore, interactions between galaxies one with another and with larger scale structure, such as galaxy cluster halos, must necessarily act through the CGM. This dissertation examines the CGM as traced by H I, C IV, and O VI absorption lines across wide range of halo environments, from isolated dwarf galaxies with M_* < 10⁸ M_sun to galaxy clusters with M_halo > 10¹⁴ M_sun. By first conducting a blind …

Spreadsheet Tools For Data Analysts, Daniel W. Barowy

Doctoral Dissertations

Spreadsheets are a natural fit for data analysis, combining a simple data storage and presentation layer with a programming language and basic debugging tools. Because spreadsheets are accessible and flexible, they are used by both novices and experts. Consequently, spreadsheets are hugely popular, with more than 750 million copies of Microsoft Excel installed worldwide. This popularity means that spreadsheets are the most popular programming language on the planet and the de facto tool for data analysis. Nevertheless, spreadsheets do not address a number of important tasks in a typical analyst's pipeline, and their design frequently complicates them. This thesis describes …

Interface Driven Dynamics And Assembly, Wei Hong

Doctoral Dissertations

Interfaces between two substances (e.g., gas / liquid, liquid / liquid) are ubiquitous in nature and industry. In this project, we study two important aspects of interface: interface driven dynamics and assembly. In the area of interface driven dynamics, we conduct experiments to study how interfacial capillarity drives flow of wax inside paper under controlled temperature and pressure. The findings lead to the ability to manufacture high-resolution paper-based microfluidic devices. In the area of interface driven assembly, we study how to tune interfacial electrostatic potential and how this potential can enhance or suppress colloidal particle assembly to the interface. We …

Synthesis And Characterization Of Imidazole-Containing Conjugated Polymers, Jared D. Harris

Doctoral Dissertations

Semiconducting conjugated polymers hold tremendous promise as active layers for transformative electronic devices. This materials class benefits from the structural variety provided by organic chemistry such that highly tunable band structures are attainable for as-synthesized polymers. This dissertation describes the synthesis and characterization of novel imidazole-containing conjugated polymers for the purposes of (de)protonating the as-synthesized materials gaining conjugated poly(ionomer)s. (De)protonation easily enables band structure modification through manipulation of the materials’ ionization potential and electron affinity. Controlled exposure to acids and bases led to reversible (de)protonation observable via UV-visible and photoluminescence spectroscopies. (De)protonation’s effects on polymeric band structures was empirically and …

Arctic And North Atlantic Paleo-Environmental Reconstructions From Lake Sediments, Gregory A. De Wet

Doctoral Dissertations

ABSTRACT

Deep Energy-Based Models For Structured Prediction, David Belanger

Doctoral Dissertations

We introduce structured prediction energy networks (SPENs), a flexible frame- work for structured prediction. A deep architecture is used to define an energy func- tion over candidate outputs and predictions are produced by gradient-based energy minimization. This deep energy captures dependencies between labels that would lead to intractable graphical models, and allows us to automatically discover discrim- inative features of the structured output. Furthermore, practitioners can explore a wide variety of energy function architectures without having to hand-design predic- tion and learning methods for each model. This is because all of our prediction and learning methods interact with the energy …

Ultraviolet To Infrared Star Formation Rate Tracers: Characterizing Dust Attenuation And Emission, Andrew Battisti

Doctoral Dissertations

Star formation rates (SFRs) are among the fundamental properties used to characterize galaxies during their evolution across cosmic times. In the first part of this dissertation, we calibrate continuous, monochromatic SFR indicators over the mid-infrared wavelength range of 6-70 micron. We use a sample of 58 local star-forming galaxies for which there is a rich suite of multi-wavelength photometry and spectroscopy from the ultraviolet through far-infrared. Our results indicate that our mid-infrared SFR indicators are applicable to galaxies over a large range of distances, proving their robustness. We have made the calibrations and diagnostics publicly available to achieve the broadest …