Physical Sciences and Mathematics Commons^™

Local Structure And Dynamic Studies Of Mixed Ch4-Co2 Gas Hydrates Via Computational Simulation And Neutron Scattering, Bernadette Rita Cladek

Doctoral Dissertations

Permeated throughout the ocean floor and arctic permafrost, natural gas hydrates contain an estimated 3000 trillion cubic meters, over three times that of traditional shale deposits, of CH₄ that is accessible for extraction. Gas hydrates are a crystal structure in which water molecules form a cage network, the host, through hydrogen bonds while trapping a guest molecule such as CH₄ in the cavities. These compounds form naturally where the appropriate low temperature and high pressure conditions occur. A promising and tested method of methane recovery is through exchange with CO₂, which energetically takes place of the …

Mixed-Precision Numerical Linear Algebra Algorithms: Integer Arithmetic Based Lu Factorization And Iterative Refinement For Hermitian Eigenvalue Problem, Yaohung Tsai

Doctoral Dissertations

Mixed-precision algorithms are a class of algorithms that uses low precision in part of the algorithm in order to save time and energy with less accurate computation and communication. These algorithms usually utilize iterative refinement processes to improve the approximate solution obtained from low precision to the accuracy we desire from doing all the computation in high precision. Due to the demand of deep learning applications, there are hardware developments offering different low-precision formats including half precision (FP16), Bfloat16 and integer operations for quantized integers, which uses integers with a shared scalar to represent a set of equally spaced numbers. …

Dynamic Neuromechanical Sets For Locomotion, Aravind Sundararajan

Doctoral Dissertations

Most biological systems employ multiple redundant actuators, which is a complicated problem of controls and analysis. Unless assumptions about how the brain and body work together, and assumptions about how the body prioritizes tasks are applied, it is not possible to find the actuator controls. The purpose of this research is to develop computational tools for the analysis of arbitrary musculoskeletal models that employ redundant actuators. Instead of relying primarily on optimization frameworks and numerical methods or task prioritization schemes used typically in biomechanics to find a singular solution for actuator controls, tools for feasible sets analysis are instead developed …

Unifying Chemistry And Machine Learning For The Study Of Noncovalent Interactions, Jacob A. Townsend

Doctoral Dissertations

Gas separations are in great demand for carbon emission reduction, natural gas purification, oxygen isolation, and much more. Many of these separations rely on cost-prohibitive methods such as cryogenic distillation or strong-binding solvents. As a result, novel materials are being developed to subvert the energetic expense of gas separation processes. These studies focus on improving the performance of alternative materials, including (but not limited to) metal-organic frameworks, covalent organic frameworks, dense polymeric membranes, porous polymers, and ionic liquids.

In this work, the atomistic effects of functional units are explored for gas separations processes using electronic structure theory and machine learning. …

Modeling User-Affected Software Properties For Open Source Software Supply Chains, Tapajit Dey

Doctoral Dissertations

Background: Open Source Software development community relies heavily on users of the software and contributors outside of the core developers to produce top-quality software and provide long-term support. However, the relationship between a software and its contributors in terms of exactly how they are related through dependencies and how the users of a software affect many of its properties are not very well understood.

Aim: My research covers a number of aspects related to answering the overarching question of modeling the software properties affected by users and the supply chain structure of software ecosystems, viz. 1) Understanding how software usage …

Using Second Harmonic Generation To Study Gram-Positive Bacterial Membranes, Lindsey N. Miller

Doctoral Dissertations

Understanding how small-molecules, such as drugs, interact with bacterial membranes can quickly unravel into much more perplexing questions. No two bacterial species are alike, especially when comparing their membrane compositions which can even be altered by incorporating fatty acids from their surrounding environment into their lipid-membrane composition. To further complicate the comparison, discrete alterations in small-molecule structures can result in vastly different membrane-interaction outcomes, giving rise to the need for more "label-free" studies when analyzing drug mechanisms. The work presented in this dissertation highlights the benefits to using nonlinear spectroscopy and microscopy techniques for probing small-molecule interactions in living bacteria. …

Characterization Of A Digital Holography Diagnostic For In Situ Erosion Measurement Of Plasma-Facing Components In Fusion Devices, Cary Dean Smith

Doctoral Dissertations

Fusion energy devices, particularly tokamaks, face the challenge of interior surface damage occurring over time from the heat flux of the high-energy plasma they generate. The ability to monitor the rate of surface modification is therefore imperative, but to date no proven technique exists for real-time erosion measurement of planar regions of interest on plasma-facing components in fusion devices. In order to fill this diagnostic gap, a digital holography system has been established at ORNL [Oak Ridge National Laboratory] for the purpose of measuring the erosion effects of plasma-material interaction in situ.

The diagnostic has been designed with the …

Benchmarks And Controls For Optimization With Quantum Annealing, Erica Kelley Grant

Doctoral Dissertations

Quantum annealing (QA) is a metaheuristic specialized for solving optimization problems which uses principles of adiabatic quantum computing, namely the adiabatic theorem. Some devices implement QA using quantum mechanical phenomena. These QA devices do not perfectly adhere to the adiabatic theorem because they are subject to thermal and magnetic noise. Thus, QA devices return statistical solutions with some probability of success where this probability is affected by the level of noise of the system. As these devices improve, it is believed that they will become less noisy and more accurate. However, some tuning strategies may further improve that probability of …

Fire-Vegetation-Climate Interactions Across The Holocene On The U.S. Southeastern Coastal Plain, Mathew S. Boehm

Doctoral Dissertations

This dissertation research examined multiple proxy indicators in sediment cores from one lake and one wetland to reconstruct long-term relationships between fire, vegetation, and climate in the southeastern U.S.

At Lake Balboa (30.6992 N, 83.2031 W; 48 m elevation), a sinkhole pond located in southern Georgia, Bølling-Allerød conditions were sufficiently wet to maintain a shallow wetland at the site. Evidence for fire was minimal. Between 12,600 and 9200 cal yr BP, water availability declined, leading to a potential hiatus in sedimentation. During the early Holocene moisture availability increased, leading to greater primary productivity within and outside the lake, triggering an …

Exploration Of Mid To Late Paleozoic Tectonics Along The Cincinnati Arch Using Gis And Python To Automate Geologic Data Extraction From Disparate Sources, Kenneth Steven Boling

Doctoral Dissertations

Structure contour maps are one of the most common methods of visualizing geologic horizons as three-dimensional surfaces. In addition to their practical applications in the oil and gas and mining industries, these maps can be used to evaluate the relationships of different geologic units in order to unravel the tectonic history of an area. The construction of high-resolution regional structure contour maps of a particular geologic horizon requires a significant volume of data that must be compiled from all available surface and subsurface sources. Processing these data using conventional methods and even basic GIS tools can be tedious and very …

Approaches To Studying Bacterial Biofilms In The Bioeconomy With Nanofabrication Techniques And Engineered Platforms., Michelle Caroline Halsted

Doctoral Dissertations

Studies that estimate more than 90% of bacteria subsist in a biofilm state to survive environmental stressors. These biofilms persist on man-made and natural surfaces, and examples of the rich biofilm diversity extends from the roots of bioenergy crops to electroactive biofilms in bioelectrochemical reactors. Efforts to optimize microbial systems in the bioeconomy will benefit from an improved fundamental understanding of bacterial biofilms. An understanding of these microbial systems shows promise to increase crop yields with precision agriculture (e.g. biosynthetic fertilizer, microbial pesticides, and soil remediation) and increase commodity production yields in bioreactors. Yet conventional laboratory methods investigate these micron-scale …

Exploring Structural And Electronic Properties Of Triangular Adatom Layers On The Silicon Surface Through Adsorbate Doping, Tyler S. Smith

Doctoral Dissertations

The analysis of the electronic structure and morphology of 1/3 monolayers (ML) of Sn or Pb on Si(111) and Ge(111) has played an important role in understanding the role of electronic correlations in two dimensions. Specifically, the two-dimensional lattice of partially filled dangling bonds of these so-called α-phases has been an important testbed for studying structural phase transitions and correlated electronic phenomena ever since the discovery of a surface charge density wave in the Pb/Ge(111) system more than two decades ago. With the exception of the novel Sn/Si(111) system, all $\alpha$-phases undergo a charge ordering transition at low temperature. The …

Numerical Studies Of Multi-Orbital Hubbard Models, Nitin Kaushal

Doctoral Dissertations

This thesis examines the emergence of exotic phases in multi-orbital Hubbard models due to competition between Coulomb interaction, spin-orbit coupling and kinetic energy. Exact diagonalization and numerically accurate density matrix renormalization group methods are used to study small clusters and one dimensional chains. Two dimensional lattices are solved using unrestricted real-space Hartree-Fock approximation. Novel excitonic insulators, due to condensation of spin-orbit excitons, are found in the spin-orbit coupling vs Coulomb interation phase diagrams of (t_2g)ⁿ systems for n = 4 and 3.5. Moreover, the presence of a BCS-BEC crossover in the (t_2g)4 excitonic insulator is …

Providing Insight To Enable The Design Of Tailored, Nano-Structured Polymeric Surfaces And Interfaces, Onome J. Agori-Iwe

Doctoral Dissertations

Methods are presented for modifying polymeric material surfaces using: 1) selective surface segregation in binary branched/linear polymer blends, and 2) surface functionalization with polymer brushes. Using neutron reflectivity, elastic recoil detection, and other complementary techniques, the aim was to identify structure-property relationships and provide fundamental insight into the time evolution and formation of surfaces and interfaces in these materials.

In blends of poly(styrene) (PS) HyperMacs and DendriMacs in a linear deuterated PS (d-PS) matrix, smaller hyperbranched additives (<1E6 g/mol) move slower than their linear analogues. Larger (>1E6 g/mol) and less flexible hyperbranched additives with smaller fractal dimensions move faster than their linear analogues, suggesting that they are less …

Dually Responsive Shape-Changing Linear And Star Molecular Bottlebrushes With Bicomponent Side Chains, Ethan Wesley Kent

Doctoral Dissertations

Molecular bottlebrushes (MBBs) can exhibit large conformational changes from wormlike to globular in solution in response to environmental stimuli. However, the instability of the collapsed state has prevented shape-changing MBBs from potential applications in, e.g., biomimetic catalysis and substance delivery. This dissertation work focused on dually responsive linear and star MBBs composed of bicomponent side chains in the form of either homografted diblock copolymer or binary heterografted polymeric side chains. When one polymer component collapsed, driving the shape changing of MBBs, another component served as a stabilizer. When both components in the side chains were stimuli-responsive, an additional level of …

Leveraging Conventional Internet Routing Protocol Behavior To Defeat Ddos And Adverse Networking Conditions, Jared M. Smith

Doctoral Dissertations

The Internet is a cornerstone of modern society. Yet increasingly devastating attacks against the Internet threaten to undermine the Internet's success at connecting the unconnected. Of all the adversarial campaigns waged against the Internet and the organizations that rely on it, distributed denial of service, or DDoS, tops the list of the most volatile attacks. In recent years, DDoS attacks have been responsible for large swaths of the Internet blacking out, while other attacks have completely overwhelmed key Internet services and websites. Core to the Internet's functionality is the way in which traffic on the Internet gets from one destination …

Mobile Location Data Analytics, Privacy, And Security, Yunhe Feng

Doctoral Dissertations

Mobile location data are ubiquitous in the digital world. People intentionally and unintentionally generate numerous location data when connecting to cellular networks or sharing posts on social networks. As mobile devices normally choose to communicate with nearby cell towers outdoor, it is reasonable to infer human locations based on cell tower coordinates. Many social networking platforms, such as Twitter, allow users to geo-tag their posts optionally, publishing personal locations to friends or everyone. These location data are particularly useful for understanding mobile usage behaviors and human mobility patterns. Meanwhile, the public expresses great concern about the privacy and security of …

Probability Distribution Of Equations Of State For Astrophysical Simulations, Xingfu Du

Doctoral Dissertations

The detection of gravitational wave during the neutron star merger event GW170817 greatly enhanced our ability to probe the interiors of neutron stars. Future measurements of similar events will put further constraints to the equation of state (EOS) of nuclear matter. Also, uncertainties in the EOS create variations in the results of astrophysical simulations of core-collapse supernovae and neutron star mergers. In order to quantify the uncertainties, we construct a probability distribution of equations of state (EOSs). We create a new EOS which respects experimental, observational and theoretical constraints on the nature of matter in various density and temperature regimes. …

Using Applications To Guide Data Management For Emerging Memory Technologies, Timothy C. Effler

Doctoral Dissertations

A number of promising new memory technologies, such as non-volatile, storage-class memories and high-bandwidth, on-chip RAMs, are emerging. Since each of these new technologies present tradeoffs distinct from conventional DRAMs, many high performance and scientific computing systems have begun to include multiple tiers of memory storage, each with their own type of devices. To efficiently utilize the available hardware, such systems will need to alter their data management strategies to consider the performance and capabilities provided by each tier. This work aims to understand and increase the effectiveness of application data management for emerging complex memory systems. A key realization …

Structure And Adsorption At The BastnäSite-Water Interface: Fundamental Investigations Toward Rare Earth Mineral Recovery, Anna Kristiina Wanhala

Doctoral Dissertations

This dissertation investigates the interfacial structure and reactivity of a rare earth mineral in the context of froth flotation. Bastnäsite [(Ce,La,Nd)FCO3], one of the primary mineral sources of rare earth elements, has been chosen for this investigation. Flotation separation relies on selective adsorption of collector ligands to the desired mineral surface in solution; fundamental understanding of these adsorption reactions will aid in the development of more effective separation technologies.

Chapter 1 presents an introduction to the significance of rare earth minerals and the process of froth flotation. Chapters 2 and 3 address the adsorption reactions of ligand molecules at the …

Lithium-Aluminum Layered Double Hydroxide Chlorides: Structural And Thermodynamic Studies To Understand Dynamics, Functionality, And Applications In Lithium Adsorption, Samuel Frederi Frederick Evans

Doctoral Dissertations

The invention of the Lithium-ion battery (LIB) has been a panacea for the development and adoption of renewable energy technologies, mobile energy storage, and electrified transportation. While LIBs have made an electrified future possible, questions have risen about the inherent "greenness" of the technology. Multiple precursor materials of LIBs are detrimental to the environment due to their production from conventional mining. This inherently contradicts the message of renewable technologies and electrification, where they are the substitute for polluting and climate altering fossil fuel industries. Without the development of sustainable and environmentally friendly processes of material extraction the "green revolution" will …

Applications With Discrete And Continuous Models: Harvesting And Contact Tracing, Danielle L. Burton

Doctoral Dissertations

Harvest plays an important role in management decisions, from fisheries to pest control. Discrete models enable us to explore the importance of timing of management decisions including the order of events of particular actions. We derive novel mechanistic models featuring explicit within season harvest timing and level. Our models feature explicit discrete density independent birth pulses, continuous density dependent mortality, and density independent harvest level at a within season harvest time. We explore optimization of within-season harvest level and timing through optimal control of these population models. With a fixed harvest level, harvest timing is taken as the control. Then …

Theoretical Modeling Of Metallic Compounds With Versatile Properties By Combining First-Principles Calculations And Global Structure Prediction Algorithms, Jinseon Park

Doctoral Dissertations

Improving the target properties of existing materials or finding new materials with enhanced functionality for practical applications is at the heart of the materials research. In this respect, the first-principles approaches, which have been successfully integrated into modern high- performance computers, have become an indispensable part of the materials research, providing a better understanding of existing materials and guidance on the design of new materials. Using state-of-the-art computational/theoretical approaches that couple global structure prediction with ab initio density functional theory calculations, we investigate structural and electronic properties of Cs_xO [cesium oxides], Li_1+xMn₂O₄ [lithium …

Bayesian Topological Machine Learning, Christopher A. Oballe

Doctoral Dissertations

Topological data analysis encompasses a broad set of ideas and techniques that address 1) how to rigorously define and summarize the shape of data, and 2) use these constructs for inference. This dissertation addresses the second problem by developing new inferential tools for topological data analysis and applying them to solve real-world data problems. First, a Bayesian framework to approximate probability distributions of persistence diagrams is established. The key insight underpinning this framework is that persistence diagrams may be viewed as Poisson point processes with prior intensities. With this assumption in hand, one may compute posterior intensities by adopting techniques …

Bioanalytical Applications Of Digital Imaging: Applications To Organ-On-Chip And Point-Of-Care Analysis Systems, Amirus Saleheen

Doctoral Dissertations

Qualitative and quantitative analysis through digital imaging has significant potential in several scientific applications including bioanalytical applications. In this document, the implication of digital imaging to validate and characterize a novel microfluidic organ-on-chip device and establish a point-of-care method to estimate epinephrine concentrations in expired and degraded autoinjectors have been described in chapter 2 and 3 respectively. Chapter 4 includes description of the principle and methodology of strong cation exchange-based immunoassay for oxytocin and β-endorphin.

In chapter 2, fabrication of a novel microfluidic organ-on-chip device capable of culturing rodent SCN slices has been discussed. Characterization of the aCSF media droplets …

Examining The Accumulation Statistics Of Index1 Saddle Points On The Potential Energy Surface And Imposing Early Termination On A Rejection Scheme For Off Lattice Kinetic Monte Carlo, Jonathan W. Hicks

Doctoral Dissertations

In the calculation of time evolution of an atomic system where a chemical reaction and/or diffusion occurs, off-lattice kinetic Monte Carlo methods can be used to overcome timescale and lattice based limitations from other methods such as Molecular Dynamics and kinetic Monte Carlo procedures. Off-lattice kinetic Monte Carlo methods rely on a harmonic approximation to Transition State Theory, in which the rate of the rare transitions from one energy minimum to a neighboring minimum require surmounting a minimum energy barrier on the Potential Energy Surface, which is found at an index-1 saddle point commonly referred to as a transition state. …

The Parity-Violating Asymmetry In The N→Δ Transition At Low Q2, Thamraa A. Alshayeb

Doctoral Dissertations

Qweak has used the parity violating asymmetry to test the Standard Model (SM) by constantly flipping helicity states of a longitudinally polarized electron beam that scatters in the unpolarized LH2 target. The main focus of the Qweak experiment at Jefferson Lab was the recently published determination of the proton’s weak charge. In order to make corrections to the measured asymmetry at low 𝑄 2 due to inelastically scattered electrons, dedicated measurements were made of the parity violating asymmetry in the N→∆ transition at two different beam energies.

The measured inelastic asymmetries are used to extract the low energy constant dΔ, …

Finding Critical And Gradient-Flat Points Of Deep Neural Network Loss Functions, Charles Gearhart Frye '09

Doctoral Dissertations

Despite the fact that the loss functions of deep neural networks are highly non-convex, gradient-based optimization algorithms converge to approximately the same performance from many random initial points. This makes neural networks easy to train, which, combined with their high representational capacity and implicit and explicit regularization strategies, leads to machine-learned algorithms of high quality with reasonable computational cost in a wide variety of domains.

One thread of work has focused on explaining this phenomenon by numerically characterizing the local curvature at critical points of the loss function, where gradients are zero. Such studies have reported that the loss functions …

Acoustic Confinement And Characterization Of A Microwave Plasma, Seth Lee Pree '09

Doctoral Dissertations

High amplitude acoustic fields are used to confine, characterize, and manipulate collisional plasmas with temperatures of a few thousand Kelvin. This dissertation describes the theory, experimental techniques, and apparatus necessary both to generate high amplitude sound in a few thousand Kelvin plasma and to use that sound field to manipulate the plasma within a resonant acoustic cavity. The acoustic field in a spherically symmetric oscillating plasma has been measured to have a Mach number of .03, which is sufficient to cause acoustic radiation pressure effects to confine the plasma to the center of its container. This field also generates convection …

Poisoning Attacks On Learning-Based Keystroke Authentication And A Residue Feature Based Defense, Zibo Wang

Doctoral Dissertations

Behavioral biometrics, such as keystroke dynamics, are characterized by relatively large variation in the input samples as compared to physiological biometrics such as fingerprints and iris. Recent advances in machine learning have resulted in behaviorbased pattern learning methods that obviate the effects of variation by mapping the variable behavior patterns to a unique identity with high accuracy. However, it has also exposed the learning systems to attacks that use updating mechanisms in learning by injecting imposter samples to deliberately drift the data to impostors’ patterns. Using the principles of adversarial drift, we develop a class of poisoning attacks, named Frog-Boiling …