Physical Sciences and Mathematics Commons^™

Impurity Production And Transport In The Prototype Material Plasma Exposure Experiment, Clyde J. Beers

Doctoral Dissertations

The Prototype Material Plasma Exposure eXperiment (Proto-MPEX) is a linear pulse plasma device at Oak Ridge National Laboratory with the purpose of doing the research and development for the heating concepts on the planned full MPEX device. The goal of MPEX is to perform material studies at fusion relevant conditions. To understand the conditions at the material target for performing plasma-material interaction studies the ion temperature and density, the electron temperature and density, and the particle flux and fluence must be known. Impurities within Proto-MPEX can alter the desired conditions at the material target and need to be understood for …

Electroweak Interactions And Fundamental Symmetries In Light Nuclei With Short-Range Effective Field Theories, Zichao Yang

Doctoral Dissertations

Effective field theories(EFTs) are powerful tools to study nuclear systems that display separation of scales. In this dissertation, we present halo EFT results for the $\beta$-delayed proton emission from $^{11}$Be, and pionless EFT results for three-nucleon systems. Halo nuclei are simply described by a tightly bound core and loosely bound valence nucleons. Using the halo EFT, we calculate the rate of the rare decay $^{11}$Be, which is a well-known halo nucleus, into $^{10}\text{Be} + p +e^- + \bar{\nu}_e$. We assume a shallow $1/2 ^+$ resonance in the $^{10}$Be$-p$ system with an energy consistent with a recent experiment by Ayyad {\it …

Auto-Curation Of Large Evolving Image Datasets, Sara Mousavicheshmehkaboodi

Doctoral Dissertations

Large image collections are becoming common in many fields and offer tantalizing opportunities to transform how research, work, and education are conducted if the information and associated insights could be extracted from them. However, major obstacles to this vision exist. First, image datasets with associated metadata contain errors and need to be cleaned and organized to be easily explored and utilized. Second, such collections typically lack the necessary context or may have missing attributes that need to be recovered. Third, such datasets are domain-specific and require human expert involvement to make the right interpretation of the image content. Fourth, the …

Total Internal Reflection: Applications In Nonlinear Microscopy And Fluorescence Anisotropy, Brandon Colon

Doctoral Dissertations

As technology advances to harness new energies and to create new cures, the sophistication of analysis grows not only in depth but in efficiency. Total internal reflection (TIR) has been coupled to microscopy leveraging its unique optical phenomenon on a breadth of topics. In this dissertation, the work presented will show how TIR was applied in two different instrumental analyses to evaluate two unique and complex systems. The first project features TIR paired with the transient absorption microscopy (TAM), a nonlinear optical technique, to gauge solvent mixing and diffusion in microreactors. Microreactors gained acclaim for their ability to produce high …

Instrument Development For High Sensitivity Size Characterization Of Lipid Vesicles And Other Biological Macromolecules Via Taylor Dispersion Analysis, Meagan Moser

Doctoral Dissertations

Just as humans communicate with other humans, the cells in our bodies communicate with each other through various, often complex, mechanisms. Cell-to-cell transmission of small molecules, lipids, proteins, peptides, or nucleic acids can be mediated by extracellular lipid vesicles called exosomes. Exosomes have been found to play a role in the delivery of regulatory molecules from one cell to another, serving as a universal communication mechanism. Currently, there is an emerging focus on characterizing exosome communication dynamics. Understanding exosome mechanisms of cell-to-cell communication requires accurate measurements of the spatiotemporal and chemical dynamics of exosome secretion. No current analytical approach offers …

Search For New Physics In Rare Higgs Boson Decays With The Cms Detector At The Large Hadron Collider, Himal Acharya

Doctoral Dissertations

A new boson with a mass of 125 GeV was discovered at the large hadron collider (LHC) in July 2012. The properties of this particle are so far consistent with the standard model (SM) expectation. Differences in the Higgs boson decay rates and predicted by the SM might indicate the presence of new particles and forces between them. Particularly, rare exclusive decays of the Higgs boson are a promising laboratory to study physics beyond the standard model. Searches for decays of the Higgs boson into a Z boson and a J/ψ meson or into pairs of J/ψ or Υ mesons …

Application Of Single-Ion Conducting Polymer Electrolytes (Sicpes), Sheng Zhao

Doctoral Dissertations

Polymer electrolytes have been widely studied as a potential candidate for next generation batterie with improved safety and higher energy density. Especially, single-ion conducting polymer electrolytes (SICPEs) have attracted significant attention due to their almost unity lithium-ion transport number, which is believed to help suppress lithium dendrite growth and extend battery cycle life. However, there is still a long way to go before they can be practically applied in batteries, due to their relatively low ionic conductivity at ambient temperature. Therefore, the main goal of this work is to explore various methods that can improve the ionic conductivity of SICPEs …

A Connectivity Framework To Explore The Role Of Anthropogenic Activity And Climate On The Propagation Of Water And Sediment At The Catchment Scale, Christos Giannopoulos

Doctoral Dissertations

Anthropogenic disturbance in intensively managed landscapes (IMLs) has dramatically altered critical zone processes, resulting in fundamental changes in material fluxes. Mitigating the negative effects of anthropogenic disturbance and making informed decisions for optimal placement and assessment of best management practices (BMPs) requires fundamental understanding of how different practices affect the connectivity or lack thereof of governing transport processes and resulting material fluxes across different landscape compartments within the hillslope-channel continuum of IMLs. However, there are no models operating at the event timescale that can accurately predict material flux transport from the hillslope to the catchment scale capturing the spatial and …

Ultrasound-Driven Fabrication Of Nanosized High-Entropy Materials For Heterogeneous Catalysis, Francis Uchenna Okejiri

Doctoral Dissertations

High-entropy materials (HEMs) have emerged as a new class of multi-principal-element materials with great technological prospects. As a unique class of concentrated solid-solution materials, HEMs, formed on the premise of incorporating five or more principal elements into a single crystalline phase, provide an excellent opportunity to access superior catalytic materials ‘hiding’ in the unexplored central regions of a multicomponent phase space of higher orders.

However, the fabrication of HEMs is energy-intensive, typically requiring extreme temperatures and/or pressures under which agglomeration of particles occurs with a commensurate decrease in surface area. For most catalytic applications, non-agglomerated particles with high surface areas …

Interfaces And Dynamics In Polymeric 3d Printing And Crystalline Polymer Blends, Stevenson C. Perryman

Doctoral Dissertations

This dissertation presents experimental work that provide a foundation to rationally improve fused filament fabrication (FFF) and immiscible blend compatibilization. Objects generated from additive manufacturing processes, such as FFF, have intrinsic structural weaknesses which include two project specific examples: structural anisotropy and irreversible thermal strain. Due to low adhesion between individual print layers that results in macroscopic defects, the mechanical strength of printed objects when force is applied perpendicular to the build orientation is drastically reduced. In the first dissertation chapter, we present a protocol to produce interlayer covalent bonds by depositing multi-amine additives between individual layers of a print …

Production Of Protactinium-229 Via Deuteron Irradiation Of Thorium-232, Naser Burahmah

Doctoral Dissertations

²²⁵Ac [Actinium-225] is a promising radionuclide for targeted alpha therapy of cancer. ²²⁹Pa can lead to the production of ²²⁹Th [Thorium-229] and ²²⁵Ac [Actinium-225]. Deuteron bombardment on natural thorium targets has been investigated to measure cross sections of protactinium isotopes. In this work, ²²⁹Pa [Protactinium-229] excitation function was measured via deuteron energies up to 50 MeV [Mega electron volt] of thin thorium foils. The irradiation took place at Lawrence Berkeley National Laboratory’s (LBNL) 88-Inch Cyclotron. The target processing and analysis were performed at Oak Ridge National Laboratory (ORNL). The target consisted of 4 thin foils …

Production And Adsorption Of Volatile Tellurium Hexafluoride, Stephanie H. Bruffey

Doctoral Dissertations

Research and development supporting the management of off-gases from nuclear fuel reprocessing has historically been focused on the off-gas streams that arise from aqueous reprocessing technology. With the advent of advanced reactor designs off-gas streams arising from advanced reprocessing methodology, such as that of FV [fluoride volatility] processing, also merit consideration. This work focuses on TeF₆ [tellurium hexafluoride], one of the most volatile radioactive compounds produced during FV, and investigates TeF₆ production, measurement, and abatement technologies.

To assist in on-line monitoring of TeF₆ by Fourier-transformed infrared spectroscopy, this work systematically used the ideal gas law and Beer’s …

Analytical Considerations And Methods For Comprehensive Analysis Of Bacterial Phospholipidomics Using Hilic-Ms/Ms, David Thomas Reeves

Doctoral Dissertations

Omics technologies have rapidly evolved over the last half century through vast improvements in efficient extraction methodologies, advances in instrumentation for data collection, and a wide assortment of informatics tools to help deconvolute sample data sets. However, there are still untapped pools of molecules that warrant further analytical attention. As the frontline defense of the cell against exterior influences, the phospholipid membrane is key in structure, defense, and signaling, but current omics studies are only just now catching up to the potential hidden within cellular lipid profiles. Examination of shifts in phospholipid speciation and character could provide researchers with a …

Exploring The Potential Of Ionothermal Syntheses For High-Performance Lithium-Ion Battery Anode Materials, Runming Tao

Doctoral Dissertations

Renewable energy storage systems are regarded as the solution to the environmental and energy crises caused by the burning of fossil fuels in vehicles. Unfortunately, owning to the limits to the electrochemical performance of the current anode materials, lithium-ion batteries [LIBs] are still lacking strength in the charging rate-capability and thereby cannot fulfill future application requirements in electrical vehicles [EVs].

Particularly, graphite with a high theoretical specific capacity of 372 mAh/g is unsuitable for EVs due to the safety concerns of passivating solid-electrolyte interphase [SEI] resulted from the low operation potential of 0.1 V versus Li/Li⁺. The other …

Audio-Driven Character Animation, Yang Zhou

Doctoral Dissertations

Generating believable character animations is a fundamentally important problem in the field of computer graphics and computer vision. It also has a diverse set of applications ranging from entertainment (e.g., films, games), medicine (e.g., facial therapy and prosthetics), mixed reality, and education (e.g., language/speech training and cyber-assistants). All these applications are all empowered by the ability to model and animate characters convincingly (human or non-human). Existing key-framing or performance capture approaches used for creating animations, especially facial animations, are either laborious or hard to edit. In particular, producing expressive animations from input speech automatically remains an open challenge. In this …

Understanding Of Visual Domains Via The Lens Of Natural Language, Chenyun Wu

Doctoral Dissertations

A joint understanding of vision and language can enable intelligent systems to perceive, act, and communicate with humans for a wide range of applications. For example, they can assist a human to navigate in an environment, edit the content of an image through natural language commands, or search through image collections using natural language queries. In this thesis, we aim to improve our understanding of visual domains through the lens of natural language. We specifically look into (1) images of categories within a fine-grained taxonomy such as species of birds or variants of aircraft, (2) images of textures that describe …

Human Mobility Monitoring Using Wifi: Analysis, Modeling, And Applications, Amee Trivedi

Doctoral Dissertations

Understanding and modeling humans and device mobility has fundamental importance in mobile computing, with implications ranging from network design and location-aware technologies to urban infrastructure planning. Today's users carry a plethora of devices such as smartphones, laptops, tablets, and smartwatches, with each device offering a different set of services resulting in different usage and mobility leading to the research question of understanding and modeling multiple user device trajectories. Additionally, prior research on mobility focuses on outdoor mobility when it is known that users spend 80% of their time indoors resulting in wide gaps in knowledge in the area of indoor …

Windows In Algebraic Geometry And Applications To Moduli, Sebastian Torres

Doctoral Dissertations

We apply the theory of windows, as developed by Halpern-Leistner and by Ballard, Favero and Katzarkov, to study certain moduli spaces and their derived categories. Using quantization and other techniques we show that stable GIT quotients of $(\mathbb{P}^1)^n$ by $PGL_2$ over an algebraically closed field of characteristic zero satisfy a rare property called Bott vanishing, which states that $\Omega^j_Y \otimes L$ has no higher cohomology for every j and every ample line bundle L. Similar techniques are used to reprove the well known fact that toric varieties satisfy Bott vanishing. We also use windows to explore derived categories of moduli …

Magnitude And Rates Of Agriculturally-Induced Soil Erosion In The Midwestern United States, Evan Thaler

Doctoral Dissertations

Fertile, agricultural productive soils are essential for producing food for a growing global population. Soil erosion diminishes soil quality, threatens food security by decreasing crop productivity, and degrades ecosystem health through increased rates of sedimentation and runoff. Despite decades and thousands of soil erosion studies, robust scalable methods for estimating the magnitude and rates of soil erosion have been elusive. In this dissertation, we develop a remote sensing method for quantifying the areal extent of historical loss in an agricultural landscape and provide a method for estimating the total thickness of soil loss and rates of historical soil loss in …

Learning From Limited Labeled Data For Visual Recognition, Jong-Chyi Su

Doctoral Dissertations

Recent advances in computer vision are in part due to the widespread use of deep neural networks. However, training deep networks require enormous amounts of labeled data which can be a bottleneck. In this thesis, we propose several approaches to mitigate this in the context of modern deep networks and computer vision tasks. While transfer learning is an effective strategy for natural image tasks where large labeled datasets such as ImageNet are available, it is less effective for distant domains such as medical images and 3D shapes. Chapter 2 focuses on transfer learning from natural image representations to other modalities. …

United States Household Carbon Footprints: Quantifying The Relationship Between Household-Level Income Inequality And Greenhouse Gas Emissions (1996-2015), Jared Starr

Doctoral Dissertations

As long as humanity has existed, we have altered our environment to provide goods, services, and (more recently) wealth to people. Over the last several centuries, the scope and pace of this transformation has accelerated with the onset of technological innovation, social and economic reorganization, and an ensuing population boom. Today, humanity’s demands on nature have become the dominant force shaping the critical earth systems upon which all life depends. From local land-use change to the global climate many of these anthropogenic pressures pose an existential threat to nature and the dependent social systems that rely on them. Yet, extreme …

Equivariant Smoothings Of Cusp Singularities, Angelica Simonetti

Doctoral Dissertations

Let $p \in X$ be the germ of a cusp singularity and let $\iota$ be an antisymplectic involution, that is an involution free on $X\setminus \{p\}$ and such that there exists a nowhere vanishing holomorphic 2-form $\Omega$ on $X\setminus \{p\}$ for which $\iota^*(\Omega)=-\Omega$. We prove that a sufficient condiition for such a singularity equipped with an antisymplectic involution to be equivariantly smoothable is the existence of a Looijenga (or anticanonical) pair $(Y,D)$ that admits an involution free on $Y\setminus D$ and that reverses the orientation of $D$.

Mathematical Model For Osteosarcoma Progression And Treatments, Trang M. Le

Doctoral Dissertations

Cancer is a complex disease where every tumor has its own characteristics, and thus different tumors may respond differently to the same treatments. Osteosarcoma, which is a rare type of cancer with poor prognosis, is especially characterized by its high heteogeneity. Therefore, it is important to study the progression of osteosarcoma tumors in different groups of patients with distinct characteristics. The immune system has been reported to play an important role in the development of various cancers with some immune cells having anti-tumor effects and others having pro-tumor effects. With recent advances in digital cytometry methods, which are techniques to …

Deep Learning Models For Irregularly Sampled And Incomplete Time Series, Satya Narayan Shukla

Doctoral Dissertations

Irregularly sampled time series data arise naturally in many application domains including biology, ecology, climate science, astronomy, geology, finance, and health. Such data present fundamental challenges to many classical models from machine learning and statistics. The first challenge with modeling such data is the presence of variable time gaps between the observation time points. The second challenge is that the dimensionality of the inputs can be different for different data cases. This occurs naturally due to the fact that different data cases are likely to include different numbers of observations. The third challenge is that different irregularly sampled instances have …

Social Measurement And Causal Inference With Text, Katherine A. Keith

Doctoral Dissertations

The digital age has dramatically increased access to large-scale collections of digitized text documents. These corpora include, for example, digital traces from social media, decades of archived news reports, and transcripts of spoken interactions in political, legal, and economic spheres. For social scientists, this new widespread data availability has potential for improved quantitative analysis of relationships between language use and human thought, actions, and societal structure. However, the large-scale nature of these collections means that traditional manual approaches to analyzing content are extremely costly and do not scale. Furthermore, incorporating unstructured text data into quantitative analysis is difficult due to …

Equivariant Surgeries And Irreducible Embeddings Of Surfaces In Dimension Four, Andrew J. Havens

Doctoral Dissertations

We construct families of smoothly irreducible embeddings of surfaces in the 4-sphere, corresponding to a range of normal Euler numbers. We also describe a procedure to produce equivariant symplectic sums of real symplectic 4-manifolds. For explicit real symplectic involutions on pairs of symplectic 4-manifolds the conditions for the existence of equivariant symplectic sums can be detected combinatorially. Such sums are sought for potential new constructions of families of irreducible knotted surfaces in fixed four manifolds.

Antibiotic Sensitivity Testing Of Foodborne Bacteria Using Surface-Enhanced Raman Spectroscopy, Joshua Gukowsky

Doctoral Dissertations

The spread of antibiotic resistant bacteria around the world has become a major public health issue, and it is essential that effective detection methods exist for identifying these organisms and preventing them from spreading throughout our food systems and into the environment. The goal of this research is to develop a novel analytical procedure that is capable of easily identifying antibiotic resistance in bacterial samples, and also provides more information about the biochemical characteristics of the bacteria and their responses to antibiotic exposure. Surface-enhanced Raman Spectroscopy (SERS), an analytical technique that uses light scattering to produce a spectrum based on …

High-Dimensional Feature Selection And Multi-Level Causal Mediation Analysis With Applications To Human Aging And Cluster-Based Intervention Studies, Hachem Saddiki

Doctoral Dissertations

Many questions in public health and medicine are fundamentally causal in that our objective is to learn the effect of some exposure, randomized or not, on an outcome of interest. As a result, causal inference frameworks and methodologies have gained interest as a promising tool to reliably answer scientific questions. However, the tasks of identifying and efficiently estimating causal effects from observed data still pose significant challenges under complex data generating scenarios. We focus on (1) high-dimensional settings where the number of variables is orders of magnitude higher than the number of observations; and (2) multi-level settings, where study participants …

Scaling Down The Energy Cost Of Connecting Everyday Objects To The Internet, Mohammad Rostami

Doctoral Dissertations

The Internet of Things (IoT) promises new opportunities for better monitoring and control of thousands of objects and sensors in households and industrial applications. The viability of large-scale IoT is, however, still a challenge given that the most widely known options for connecting everyday objects, i.e. duty-cycled active radios such as WiFi, Bluetooth and Zigbee, are power-hungry and increase the cost of deployment and maintenance of the connected devices. The main argument of this thesis is that passive radios that use backscatter communication, which has been used primarily for RFIDs, can fill this gap as an ultra-low power replacement for …

Robust Algorithms For Clustering With Applications To Data Integration, Sainyam Galhotra

Doctoral Dissertations

A growing number of data-based applications are used for decision-making that have far-reaching consequences and significant societal impact. Entity resolution, community detection and taxonomy construction are some of the building blocks of these applications and for these methods, clustering is the fundamental underlying concept. Therefore, the use of accurate, robust and scalable methods for clustering cannot be overstated. We tackle the various facets of clustering with a multi-pronged approach described below. 1. While identification of clusters that refer to different entities is challenging for automated strategies, it is relatively easy for humans. We study the robustness of clustering methods that …