Physical Sciences and Mathematics Commons^™

Photothermal And Photochemical Strategies For Lightinduced Shape-Morphing Of Soft Materials, Alexa Simone Kuenstler

Doctoral Dissertations

Engineering materials with the capability to transform energy from photons into mechanical work is an outstanding technical challenge with implications across myriad disciplines. Despite decades of work in this area, comprehensive understanding of how to prescribe shape change and work output in photoactive systems remains limited. To this end, this dissertation explores strategies to assemble photothermal and photochemical moieties in soft material systems to fabricate photoaddressable devices capable of specific shape changes upon illumination. Chapters 2 and 3 describe a methodology for spatially patterning plasmonic nanoparticles in liquid crystal elastomer fibers and sheets to specify local photothermally-induced strain profiles. Using …

Reasoning About User Feedback Under Identity Uncertainty In Knowledge Base Construction, Ariel Kobren

Doctoral Dissertations

Intelligent, automated systems that are intertwined with everyday life---such as Google Search and virtual assistants like Amazon’s Alexa or Apple’s Siri---are often powered in part by knowledge bases (KBs), i.e., structured data repositories of entities, their attributes, and the relationships among them. Despite a wealth of research focused on automated KB construction methods, KBs are inevitably imperfect, with errors stemming from various points in the construction pipeline. Making matters more challenging, new data is created daily and must be integrated with existing KBs so that they remain up-to-date. As the primary consumers of KBs, human users have tremendous potential to …

Understanding The Dynamic Visual World: From Motion To Semantics, Huaizu Jiang

Doctoral Dissertations

We live in a dynamic world, which is continuously in motion. Perceiving and interpreting the dynamic surroundings is an essential capability for an intelligent agent. Human beings have the remarkable capability to learn from limited data, with partial or little annotation, in sharp contrast to computational perception models that rely on large-scale, manually labeled data. Reliance on strongly supervised models with manually labeled data inherently prohibits us from modeling the dynamic visual world, as manual annotations are tedious, expensive, and not scalable, especially if we would like to solve multiple scene understanding tasks at the same time. Even worse, in …

Composite Network Of Actin And Microtubule Filaments, Self-Organization And Steady-State Dynamics, Leila Farhadi

Doctoral Dissertations

Actin and microtubule filaments, with their auxiliary proteins, enable the cytoskeleton to perform vital processes in the cell by tuning the organizational, mechanical properties and dynamics of the network. Despite their critical importance and interactions in cells, we are only beginning to uncover information about the composite network. Here, I use florescence microscopy to explore the role of filaments characteristics, interactions and activities in the self-organization and steady-state dynamics of the composite network of filaments. First, I discuss active self-organization of semiflexible actin and rigid microtubule filaments in the 2D composite network while myosin II and kinesin-1 motor proteins propel …

Engineering Stimuli-Responsive Polymeric Nanoassemblies: Rational Designs For Intracellular Delivery Of Biologics, Kingshuk Dutta

Doctoral Dissertations

Biologic drugs have gained enormous research attention in recent years as reflected by the development of multiple candidates to the clinical pipelines and an increased percentage of FDA approval. This is reasoned by the fact that biologics have been proven to deliver more predictive and promising benefits for many hard-to-cure diseases by ‘drugging the undruggable’ targets. However, the challenges associated with biologic drug development are multi-fold, viz, poor encapsulation efficacy, systemic instability, low cellular internalization and endosomal escape capability. Thus, it is essential to develop new molecular strategies that can not only address the associated drug delivery challenges, but also …

Distortion-Controlled Isotropic Swelling And Self-Assembly Of Triply-Periodic Minimal Surfaces, Carlos M. Duque

Doctoral Dissertations

In the first part of this thesis, I propose a method that allows us to construct optimal swelling patterns that are compatible with experimental constraints. This is done using a greedy algorithm that systematically increases the perimeter of the target surface with the help of minimum length cuts. This reduces the areal distortion that comes from the changing Gaussian curvature of the sheet. The results of our greedy cutting algorithm are tested on surfaces of constant and varying Gaussian curvature, and are additionally validated with finite thickness simulations using a modified Seung-Nelson model. In the second part of the thesis, …

Searching For New Physics At Colliders And From Precision Measurements, Yong Du

Doctoral Dissertations

Beyond the great triumph of the Standard Model of particle physics, several fundamental questions remain unknown with the framework of the Standard Model. Among them are the non-zero neutrino masses, the dark matter and the baryon asymmetry of the Universe. Answers to these questions require new physics beyond the Standard Model and searching for the new physics beyond the SM has been a major task for modern particle physicists. The signal of this new physics can be searched through colliders, low- and high-energy precision measurements, as well as precision cosmological observation. Here I present my work in searching for the …

Experimental Study Of Viscoelastic Fluid-Structure Interactions, Anita Anup Dey

Doctoral Dissertations

It is well known that when a flexible or flexibly-mounted structure is placed perpendicular to a Newtonian fluid flow, it can oscillate due to the shedding of vortices at high Reynolds numbers. Unlike Newtonian fluids, viscoelastic fluid flow can become unstable even at infinitesimal Reynolds numbers due to a purely elastic flow instability occurring at large Weissenberg numbers. This thesis focuses on exploring the mechanisms of viscoelastic fluid-structure interactions (VFSI) through experimental investigations on several different combinations of flexible and flexibly-mounted circular cylinders, micro and macro-scale cantilevered beams and viscoelastic fluids such as wormlike micelle solutions and polymer solutions. VFSI …

Engineered Proteins As Tools To Understand Ubiquitin Signaling, Lin Hui Chang

Doctoral Dissertations

Ubiquitin is a 76 amino acids protein that is evolutionary conserved in eukaryotes. It is an important signaling molecule in a plethora biological events, such as protein degradation, DNA damage response, and transcription. This thesis aims to develop engineered protein as a tool to study ubiquitin signaling. Through targeted mutagenesis and directed evolution, a deubiquitinase is reprogrammed into a transamidase, which lead to the generation of ubiquitinprotein conjugates with discrete ubiquitin linkages through auto-ubiquitination. These ubiquitin-protein conjugates could be used as a model substrate to profile their interaction of different ubiquitin interacting proteins. In addition, using directed evolution and deep …

Theory And Improved Methods For Probing The Cavitation To Fracture Transition, Christopher Barney

Doctoral Dissertations

A material is considered soft when its bulk modulus is significantly greater than its shear modulus. Rubbery polymers are a class of soft materials where resistance to extension is mainly entropic in nature. Polymeric soft solids differ from liquids due to the presence of a percolated network of strong bonds that resist deformation and flow on a given time scale. The incompressible nature, entropically driven elasticity, and molecular scale network structure of soft polymeric solids combine to impart unique mechanical behavior that often results in complex material responses to simple loading situations. An important example of this is cavitation in …

Filaments, Fibers, And Foliations In Frustrated Soft Materials, Daria Atkinson

Doctoral Dissertations

Assemblies of one-dimensional filaments appear in a wide range of physical systems: from biopolymer bundles, columnar liquid crystals, and superconductor vortex arrays; to familiar macroscopic materials, like ropes, cables, and textiles. Interactions between the constituent filaments in such systems are most sensitive to the distance of closest approach between the central curves which approximate their configuration, subjecting these distinct assemblies to common geometric constraints. Dual to strong dependence of inter-filament interactions on changes in the distance of closest approach is their relative insensitivity to reptations, translations along the filament backbone. In this dissertation, after briefly reviewing the mechanics and …

Transitions Between Radial And Bipolar Liquid Crystal Drops In The Presence Of Novel Surfactants, Jake Shechter

Doctoral Dissertations

Liquid crystals (LCs) are a class of molecules that form a variety of configurations easily influenced by external interactions. Of particular interest are rod-like LC molecules confined to a spherical geometry, which have a competition between interfacial tension and elastic deformations. The configuration of the liquid crystal inside a droplet can be controlled using surfactants, influencing the boundary conditions, in an oil-in-water emulsion. I tested the effects of novel surfactants on the configuration of the LC droplets. These novel surfactant molecules, synthesized by collaborators, are oligomers with either a variable length hydrophobic domain or protein sensitive hydrophilic domain. I tested …

Analysis Of Titanium Dioxide Nanoparticles In Foods Using Raman Spectroscopic Techniques, Janamkumar Pandya

Doctoral Dissertations

Titanium dioxide (TiO2) and its nanoparticles (NPs) are widely used in various applications. Recently, the presence of TiO2 NPs in food and consumer products raised safety concerns to human health and the environment. The goal of this project is to explore the capability of Raman Spectroscopy in the analysis of TiO2-NPs and apply this technique for the analysis of TiO2-NPs in food and environmental samples. Two approaches, i.e. the ligand-based and the mapping-based, were evaluated. The ligand-based approach utilized the surface enhanced Raman scattering (SERS) property of the TiO2 NPs as a substrate to enhance the signal of a surface …

Controlled Membrane Remodeling By Nanospheres And Nanorods: Experiments Targeting The Design Principles For Membrane-Based Materials, Sarah Zuraw-Weston

Doctoral Dissertations

In this thesis we explore two experimental systems probing the interactions of nanoparticles with lipid bilayer membranes. Inspired by the ability of cell membranes to alter their shape in response to bound particles, we report two experimental studies: one of nanospheres the other of long, slender nano-rods binding to lipid bilayer vesicles and altering the membrane shape. Our work illuminates the role of particle geometry, particle concentration, adhesion strength and membrane tension in how membrane morphology is determined. We combine giant unilamellar vesicles with oppositely charged nanoparticles, carefully tuning adhesion strength, membrane tension and particle concentration. In the case of …

Investigating The Accumulation, Sub-Organ Distribution, And Biochemical Effects Of Nanomaterials Using Mass Spectrometry, Kristen Nicole Sikora

Doctoral Dissertations

Gold nanoparticles (AuNPs) are attractive materials for use in various biomedical applications, such as therapeutic delivery, due to their unique chemical properties and modular tunability. Mass spectrometry methods, including laser desorption/ionization mass spectrometry (LDI-MS) and inductively coupled plasma mass spectrometry (ICP-MS) have been successfully used to evaluate the distribution of AuNPs in complex biological systems. As new AuNP-based materials are developed for applications in therapeutic delivery, it is essential to simultaneously develop analytical techniques that can comprehensively assess their behavior in vivo. In this dissertation, novel mass spectrometric methods have been developed and utilized to evaluate the uptake, distribution, …

Implications And Significance Of Partial Melting On The Tectonic History Of The Eastern Adirondack Mountains, Claire Rose Pless

Doctoral Dissertations

The eastern Adirondack Mountains contain abundant exposures of high-grade metamorphic rocks. These exposures are interpreted to be a window into the mid/deep crust of an ancient, large, hot, long-duration orogen, allowing the Adirondack Mountains to be used as an analogue to the deep processes of modern orogens. Currently interpreted thermo-tectonic events in the eastern Adirondack Mountains include the ca. 1245-1220 Ma Elzevirian orogeny, the ca. 1190-1150 Ma Shawinigan orogeny, emplacement of the ca. 1150 Ma AMCG igneous suite, the ca. 1090-1050 Ma Ottawan orogeny, and a ca. 1050-1020 Ma extensional collapse phase. This dissertation focuses on six migmatite domains within …

System Design For Digital Experimentation And Explanation Generation, Emma Tosch

Doctoral Dissertations

Experimentation increasingly drives everyday decisions in modern life, as it is considered by some to be the gold standard for determining cause and effect within any system. Digital experiments have expanded the scope and frequency of experiments, which can range in complexity from classic A/B tests to contextual bandits experiments, which share features with reinforcement learning. Although there exists a large body of prior work on estimating treatment effects using experiments, this prior work did not anticipate the new challenges and opportu- nities introduced by digital experimentation. Novel errors and threats to validity arise at the intersection of software and …

Algorithms For Massive, Expensive, Or Otherwise Inconvenient Graphs, David Tench

Doctoral Dissertations

A long-standing assumption common in algorithm design is that any part of the input is accessible at any time for unit cost. However, as we work with increasingly large data sets, or as we build smaller devices, we must revisit this assumption. In this thesis, I present some of my work on graph algorithms designed for circumstances where traditional assumptions about inputs do not apply.
1. Classical graph algorithms require direct access to the input graph and this is not feasible when the graph is too large to fit in memory. For computation on massive graphs we consider the dynamic …

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 …

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 …

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. …

Laser-Induced Breakdown Spectroscopy And Plasmas Containing Cyanide, Christopher Matthew Helstern

Doctoral Dissertations

This dissertation focuses on laser-induced plasma of diatomic molecular cyanide. Optical breakdown plasma generation is produced by high-peak-power 1064 nm Q-switched nanosecond pulsed radiation. Laser-induced breakdown is performed on a 1:1 molar gas mixture of carbon dioxide and nitrogen held at a fixed pressure of 760 Torr, a 1:1 molar gas mixture of carbon dioxide and nitrogen held at a fixed pressure of 2069 Torr, and a flowing 1:1 molar gas mixture of carbon dioxide and nitrogen flowing at a rate of 100 mL per minute. Plasma shockwave measurements in laboratory air are shown to determine the shock front geometry …

Application Of Crowdsourced Data In Transportation Operations And Safety, Nima Hoseinzadeh

Doctoral Dissertations

Crowdsourcing refers to the acquisition of data from users who contribute their information via smartphone, social media, or the internet. In transportation systems, crowdsourcing turns users into real-time sensors, providing data on traffic speed, travel time, mile traveled, incidents, roadway conditions, weather severity, irregularities in traffic patterns, and hazards. These data can be collected actively or passively in quantitative or qualitative forms. With the emergence of smartphones and navigation apps, crowdsourced data are gaining increased attention in transportation. Crowdsourced data have advantages over traditional fixed-location sensors and camera monitoring: low implementation costs, extended geographic coverage, high resolution, real-time application, increased …

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 …

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 …

Nonparametric Bayesian Deep Learning For Scientific Data Analysis, Devanshu Agrawal

Doctoral Dissertations

Deep learning (DL) has emerged as the leading paradigm for predictive modeling in a variety of domains, especially those involving large volumes of high-dimensional spatio-temporal data such as images and text. With the rise of big data in scientific and engineering problems, there is now considerable interest in the research and development of DL for scientific applications. The scientific domain, however, poses unique challenges for DL, including special emphasis on interpretability and robustness. In particular, a priority of the Department of Energy (DOE) is the research and development of probabilistic ML methods that are robust to overfitting and offer reliable …

Probing Structure, Function And Dynamics In Bacterial Primary And Secondary Transporter-Associated Binding Proteins, Shantanu Shukla

Doctoral Dissertations

Substrate binding proteins (SBPs) are ubiquitous in all life forms and have evolved to perform diverse physiological functions, such as in membrane transport, gene regulation, neurotransmission, and quorum sensing. It is quite astounding to observe such functional diversity among the SBPs even when they are restricted by their fold space. Therefore, the SBPs are an excellent set of proteins that can reveal how proteins evolution novel function in a structurally conserved/constrained fold. This study attempts to understand the phenomenon of affinity and specificity evolution in SBPs by combining a set of biochemical, biophysical, and structural studies on the SBPs involved …

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 …

Root Stage Distributions And Their Importance In Plant-Soil Feedback Models, Tyler Poppenwimer

Doctoral Dissertations

Roots are fundamental to PSFs, being a key mediator of these feedbacks by interacting with and affecting the soil environment and soil microbial communities. However, most PSF models aggregate roots into a homogeneous component or only implicitly simulate roots via functions. Roots are not homogeneous and root traits (nutrient and water uptake, turnover rate, respiration rate, mycorrhizal colonization, etc.) vary with age, branch order, and diameter. Trait differences among a plant’s roots lead to variation in root function and roots can be disaggregated according to their function. The impact on plant growth and resource cycling of changes in the distribution …

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 …