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Doctoral Dissertations

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The Impact Of A Nuclear Disturbance On A Space-Based Quantum Network, Alexander Miloshevsky Dec 2022

The Impact Of A Nuclear Disturbance On A Space-Based Quantum Network, Alexander Miloshevsky

Doctoral Dissertations

Quantum communications tap into the potential of quantum mechanics to go beyond the limitations of classical communications. Currently, the greatest challenge facing quantum networks is the limited transmission range of encoded quantum information. Space-based quantum networks offer a means to overcome this limitation, however the performance of such a network operating in harsh conditions is unknown. This dissertation analyzes the capabilities of a space-based quantum network operating in a nuclear disturbed environment. First, performance during normal operating conditions is presented using Gaussian beam modeling and atmospheric modeling to establish a baseline to compare against a perturbed environment. Then, the DEfense …


Core-Collapse Supernova Simulations With Spectral Two-Moment Neutrino Transport, Ran Chu Dec 2022

Core-Collapse Supernova Simulations With Spectral Two-Moment Neutrino Transport, Ran Chu

Doctoral Dissertations

The primary focus of this dissertation is to develop a next-generation, state-of-the-art neutrino kinetics capability that will be used in the context of the next-generation, state-of-the-art core-collapse supernova (CCSN) simulation frameworks \thornado\ and \FLASH.\index{CCSN} \thornado\ is a \textbf{t}oolkit for \textbf{h}igh-\textbf{or}der \textbf{n}eutrino-r\textbf{ad}iation hydr\textbf{o}dynamics, which is a collection of modules that can be incorporated into a simulation code/framework, such as \FLASH, together with a nuclear equation of state (EOS)\index{EOS} library, such as the \WeakLib\ EOS tables. The first part of this work extends the \WeakLib\ code to compute neutrino interaction rates from~\cite{Bruenn_1985} and produce corresponding opacity tables.\index{Bruenn 1985} The processes of emission, …


On Interpreting Eddy Covariance In Small Area Agricultural Situations With Contrasting Site Management., Joel Oetting Dec 2022

On Interpreting Eddy Covariance In Small Area Agricultural Situations With Contrasting Site Management., Joel Oetting

Doctoral Dissertations

This dissertation examined the carbon sequestration potential of a low C:N soil amendment and its incorporation into the soil over a rolling agricultural field. A segmented planar fit was developed to assess and correct the systematic errors the topography introduces on the carbon dioxide fluxes. The carbon dioxide fluxes were then be partitioned into gross primary productivity and soil respiration to understand the influence of the contrasting management practices, using flux variance partitioning. Concomitant with the partitioning, high resolution temporal and spatial scale remote sensing images were interpolated and standardized to conduct hypothesis testing for treatment effects.


Transition Metal Computational Catalysis: Mechanistic Approaches And Development Of Novel Performance Metrics, Brett Anthony Smith Dec 2022

Transition Metal Computational Catalysis: Mechanistic Approaches And Development Of Novel Performance Metrics, Brett Anthony Smith

Doctoral Dissertations

Computational catalysis is an ever-growing field, thanks in part to the incredible progression of computational power and the efficiency offered by our current methodologies. Additionally, the accuracy of computation and the emergence of new methods that can decompose energetics and sterics into quantitative descriptors has allowed for researchers to begin to identify important structure-function relationships that predict the properties of unexplored subspaces within the overall chemical space. Catalytic descriptors have been used frequently in data driven high-throughput computational screenings. With the use of machine learning, a large portion of the chemical space an be predicted in matter of minutes or …


Elucidating The Importance Of Structure, Surfaces, And Interfaces In Polymer Nanoparticles And Nanocomposites, Jacob E. Fischer Dec 2022

Elucidating The Importance Of Structure, Surfaces, And Interfaces In Polymer Nanoparticles And Nanocomposites, Jacob E. Fischer

Doctoral Dissertations

This dissertation details research conducted to elucidate the importance of structure, surfaces, and interfaces in both polymeric nanoparticles and polymer nanocomposites. The fundamental understanding that is garnered in these studies provides a foundation to rationally develop nanocomposites tailored for unique functionalities, performance and applications.

Soft polymeric nanoparticles, have shown to imbue non-traditional diffusive properties, the strength of which decreases with crosslinking density of the nanoparticle. The crosslinking dependent morphology of these nanoparticles is first characterized in a dilute solution of good solvent (Chapter 2). The scattering results revealed that the structure ranges from a swollen polymer in good solvent (0% …


Controlling Polymer Molecular Structure And Morphology: From Illumination Of Conjugated Polymers To Polymer Chain Depolymerization, Josh Moncada Dec 2022

Controlling Polymer Molecular Structure And Morphology: From Illumination Of Conjugated Polymers To Polymer Chain Depolymerization, Josh Moncada

Doctoral Dissertations

Polymers remain a prominent component of our lives, and finding methods to control their structure or morphology are needed to tune material properties. This dissertation reports methods to alter the conformation, morphology, or structure of polymeric materials. Chapter two describes the impact of exposure to white light during annealing of conjugated polymer blends on their morphology and optoelectronic performance. The observed changes in the morphology correlate strongly to the variation in photoluminescence (PL) with illumination, including that the PL varies less with illumination at higher Poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] loadings, offering foundational understanding to guide the structure and optoelectronic performance of conjugated polymer …


Constrained Collective Movement In Human-Robot Teams, Joshua Fagan Dec 2022

Constrained Collective Movement In Human-Robot Teams, Joshua Fagan

Doctoral Dissertations

This research focuses on improving human-robot co-navigation for teams of robots and humans navigating together as a unit while accomplishing a desired task. Frequently, the team’s co-navigation is strongly influenced by a predefined Standard Operating Procedure (SOP), which acts as a high-level guide for where agents should go and what they should do. In this work, I introduce the concept of Constrained Collective Movement (CCM) of a team to describe how members of the team perform inter-team and intra-team navigation to execute a joint task while balancing environmental and application-specific constraints. This work advances robots’ abilities to participate along side …


Development Of A New High-Resolution Neutron Detector And Beta-Delayed Neutron Spectroscopy Of 24o., Shree K. Neupane Dec 2022

Development Of A New High-Resolution Neutron Detector And Beta-Delayed Neutron Spectroscopy Of 24o., Shree K. Neupane

Doctoral Dissertations

An efficient neutron detection system with good energy resolution is needed to correctly characterize the decays of neutron-rich nuclei where beta-delayed neutron emission is a dominant decay mode. Precision neutron spectroscopy probes nuclear structure effects in neutron-rich nuclei and is essential to exploit the opportunities in new-generation radioactive beam facilities. A new high-resolution neutron detector, Neutron dEtector with Xn Tracking (NEXT), has been constructed, characterized, and tested in decay and reaction experiments. Its essential capability is the neutron interaction position localization, which enables improvement in energy resolution without compromising detection efficiency in the time-of-flight measurements. Neutron-gamma discrimination capability of NEXT …


Imaging Normal Fluid Flow In He Ii With Neutrons And Lasers — A New Application Of Neutron Beams For Studies Of Turbulence, Xin Wen Dec 2022

Imaging Normal Fluid Flow In He Ii With Neutrons And Lasers — A New Application Of Neutron Beams For Studies Of Turbulence, Xin Wen

Doctoral Dissertations

Turbulence is ubiquitous in life —from biology to astrophysics. The best direct numeric simulations (DNS) have only been benchmarked against low resolution, time-averaged experimental configurations—partly because of limitations in computing power. With time, computing power has greatly increased, so there is need for higher quality data of turbulent flow. In this dissertation, we explore a solution that enables quantitative visualization measurement of the velocity field in liquid helium, which has the potential of breaking new ground for high Reynolds number turbulence research and model testing.

Our technique involves creation of clouds of molecular tracers using 3He-neutron absorption reaction in liquid …


Towards Reduced-Order Model Accelerated Optimization For Aerodynamic Design, Andrew L. Kaminsky Dec 2022

Towards Reduced-Order Model Accelerated Optimization For Aerodynamic Design, Andrew L. Kaminsky

Doctoral Dissertations

The adoption of mathematically formal simulation-based optimization approaches within aerodynamic design depends upon a delicate balance of affordability and accessibility. Techniques are needed to accelerate the simulation-based optimization process, but they must remain approachable enough for the implementation time to not eliminate the cost savings or act as a barrier to adoption.

This dissertation introduces a reduced-order model technique for accelerating fixed-point iterative solvers (e.g. such as those employed to solve primal equations, sensitivity equations, design equations, and their combination). The reduced-order model-based acceleration technique collects snapshots of early iteration (pre-convergent) solutions and residuals and then uses them to project …


Evaluation Of Distributed Programming Models And Extensions To Task-Based Runtime Systems, Yu Pei Dec 2022

Evaluation Of Distributed Programming Models And Extensions To Task-Based Runtime Systems, Yu Pei

Doctoral Dissertations

High Performance Computing (HPC) has always been a key foundation for scientific simulation and discovery. And more recently, deep learning models' training have further accelerated the demand of computational power and lower precision arithmetic. In this era following the end of Dennard's Scaling and when Moore's Law seemingly still holds true to a lesser extent, it is not a coincidence that HPC systems are equipped with multi-cores CPUs and a variety of hardware accelerators that are all massively parallel. Coupling this with interconnect networks' speed improvements lagging behind those of computational power increases, the current state of HPC systems is …


Intra-Skeletal Variation In Stable Isotopes Through Non-Destructive Approaches: Applications Of The Patterns Of Skeletal Remodeling To Biological Anthropology, Armando Anzellini Dec 2022

Intra-Skeletal Variation In Stable Isotopes Through Non-Destructive Approaches: Applications Of The Patterns Of Skeletal Remodeling To Biological Anthropology, Armando Anzellini

Doctoral Dissertations

Stable isotope analysis is a well-established method in biological anthropology used to deliver data on residence, diet, and life history. Samples for these analyses are often collected from the diaphyses of long bones with an assumption of an expected rate of turnover between five and ten years, depending on the skeletal element. However, the biological foundations of this assumption are still uncertain, especially concerning the intra-skeletal and intra-element variation of isotopic signatures that may relate to patterns of remodeling. Exploring these gaps in intra-element isotopic variation requires fine-grained work using multiple bones from multiple individuals, but such work is limited …


Natural, Experimental, And Educational Explorations Of The Interiors Of Terrestrial Planetary Bodies, Nadine L. Grambling Dec 2022

Natural, Experimental, And Educational Explorations Of The Interiors Of Terrestrial Planetary Bodies, Nadine L. Grambling

Doctoral Dissertations

Planetary interiors are enigmatic, inaccessible, and vital to the processes that have formed the rocks we see on the surface of bodies in the inner Solar System today. Based on geophysical explorations of the Moon and Earth, along with information gleaned from rocks at the surface today, there is understanding of the basic structure and processes at depth. Using a combination of natural samples and experimental studies, we attempt to learn more about the physical conditions beneath the surface, and their effect on material properties and tectonics processes in the mantle.

On Earth, mid-ocean ridge processes have long been debated, …


Tethered Axial Coordination As A Control Modality In Rhodium(Ii)-Catalyzed Carbene Transfer Reactions, Anthony Dean Abshire Dec 2022

Tethered Axial Coordination As A Control Modality In Rhodium(Ii)-Catalyzed Carbene Transfer Reactions, Anthony Dean Abshire

Doctoral Dissertations

Rhodium(II) paddlewheels are versatile carbene transfer catalyst that are broadly applied in insertion reactions, cycloadditions, and ylide transformations. The effects of axial coordination in rhodium(II)-catalyzed carbene transfer reactions are still little understood due to compounding factors that are difficult to isolate. Traditionally, researchers study axial coordination by addition of Lewis base additives. To ensure interaction between the Lewis base and catalyst, high molar equivalents are used. This can also have the undesired effect of hampering the activity of the catalyst and suppressing the yield of the reaction. We have developed ligands with a tethered Lewis base to overcome these issues. …


The Novel Chlorination Of Zirconium Metal And Its Application To A Recycling Protocol For Zircaloy Cladding From Spent Nuclear Fuel Rods, Breanna K. Vestal Dec 2022

The Novel Chlorination Of Zirconium Metal And Its Application To A Recycling Protocol For Zircaloy Cladding From Spent Nuclear Fuel Rods, Breanna K. Vestal

Doctoral Dissertations

A novel protocol has been developed for the chemical removal of zirconium alloy (Zircaloy) cladding from spent nuclear fuel rods and subsequent isolation and purification of nuclear-grade zirconium chloride derived therefrom. This protocol is based on the chemistry developed from two new scientific findings.

First, two new oxidative chlorination reactions have been discovered for zirconium metal. In both solvents, zirconium can be quantitatively chlorinated at temperatures less than 150°C, with the operative equations seen below. In sulfur monochloride, the reaction is completed in 2 – 4 hours via surface etching, exhibiting 0th order kinetic behavior. The elemental sulfur byproduct …


Analytical Techniques For The Analysis Of Uranium Bearing Materials, Nathaniel D. Fletcher Dec 2022

Analytical Techniques For The Analysis Of Uranium Bearing Materials, Nathaniel D. Fletcher

Doctoral Dissertations

The interest in the use of nuclear power has increased drastically in recent years. This is due to significantly increased efficiency at producing energy when compared to fossil fuels. With the increased use of nuclear power comes an increased need to for monitor for uranium bearing materials outside of regulatory control. This dissertation covers four projects aimed at improving the analysis of these materials. The first projects aims to develop a method that allows for the analysis of elements that exist in nature as anions by triple quadrupole ICP – MS. This would allow for the ability to measure more …


Geochemical And Climatic Controls On The Sulfur Cycle In Volcanic Settings: Implications For The Origin Of Sulfur-Rich Deposits Investigated By The Spirit And Opportunity Rovers On Mars, Rhianna D. Moore Dec 2022

Geochemical And Climatic Controls On The Sulfur Cycle In Volcanic Settings: Implications For The Origin Of Sulfur-Rich Deposits Investigated By The Spirit And Opportunity Rovers On Mars, Rhianna D. Moore

Doctoral Dissertations

On Earth, volcanic activity with elevated sulfur (S) degassing in the presence of water leads to the formation of hydrothermal deposits enriched in S-bearing minerals. Similar processes may have been an important source of S on Mars. The landing sites of Gusev crater and Meridiani Planum investigated by the Spirit and Opportunity rovers, respectively, showed elevated SO42- [sulfate] concentrations, suggesting high- and low-temperature aqueous processes. However, the SO42- contribution from subsequent aqueous weathering of hydrothermal S deposits has been poorly constrained, thus its importance to regional S cycling in the landing sites is unclear. In this …


Light Matter Interactions: A Study Of Soft Materials Using Linear And Nonlinear Spectroscopy, Muhammad Redwan Hassan Dec 2022

Light Matter Interactions: A Study Of Soft Materials Using Linear And Nonlinear Spectroscopy, Muhammad Redwan Hassan

Doctoral Dissertations

The adoption of complex fluids for various industrial applications is becoming normal. Complex fluids offer tunability, wide range solubility, and chemical and thermal stability which are the factors that conventional polar and non-polar solvents often lack. However, fundamental studies of these fluid systems are still lacking which is limiting the appropriate use of these complex fluids in many applications. The goal of this dissertation was to study and characterize complex fluids for application in electrolytes for redox flow batteries. Chapter 3 and chapter 4 feature the study of microemulsions and deep eutectic solvents (DES) by fluorescence techniques. Fluorescence studies of …


Experimental Approaches To Evaluating Silicate Melt Properties And Trace Element Fractionation During Crystallization At High Pressures And High Temperatures, Megan D. Mouser Dec 2022

Experimental Approaches To Evaluating Silicate Melt Properties And Trace Element Fractionation During Crystallization At High Pressures And High Temperatures, Megan D. Mouser

Doctoral Dissertations

Current understanding of the evolution and behavior of silicate materials that form in planetary interiors at high-pressures and high-temperatures largely come from experimental work as natural samples are either rare, or physically inaccessible. Laboratory experiments provide a comprehensive way to constrain the crystallization history, elemental partitioning, and viscosity of different silicate materials at planetary mantle pressure and temperature conditions. This work utilizes two high-pressure experimental techniques, the Paris-Edinburgh apparatus, and the piston cylinder apparatus, to measure physical and chemical properties of silicate materials. The viscosity of reduced, Fe-free silicate liquids, with and without sulfur (S-free and S-bearing), were measured to …


Enhancing The Performance Of The Mtcnn For The Classification Of Cancer Pathology Reports: From Data Annotation To Model Deployment, Kevin De Angeli Dec 2022

Enhancing The Performance Of The Mtcnn For The Classification Of Cancer Pathology Reports: From Data Annotation To Model Deployment, Kevin De Angeli

Doctoral Dissertations

Information contained in electronic health records (EHR) combined with the latest advances in machine learning (ML) have the potential to revolutionize the medical sciences. In particular, information contained in cancer pathology reports is essential to investigate cancer trends across the country. Unfortunately, large parts of information in EHRs are stored in the form of unstructured, free-text which limit their usability and research potential. To overcome this accessibility barrier, cancer registries depend on expert personnel who read, interpret, and extract relevant information. Naturally, as the number of stored pathology reports increases every day, depending on human experts presents scalability challenges. Recently, …


Symmetry Breaking Effects In Low-Dimensional Quantum Systems, Ke Wang Oct 2022

Symmetry Breaking Effects In Low-Dimensional Quantum Systems, Ke Wang

Doctoral Dissertations

Quantum criticality in low-dimensional quantum systems is known to host exotic behaviors. In quantum one-dimension (1D), the emerging conformal group contains infinite generators, and conformal techniques, e.g., operator product expansion, give accurate and universal descriptions of underlying systems. In quantum two-dimension (2D), the electronic interaction causes singular corrections to Fermi-liquids characteristics. Meanwhile, the Dirac fermions in topological 2D materials can greatly enrich emerging phenomena. In this thesis, we study the symmetry-breaking effects of low-dimensional quantum criticality. In 1D, we consider two cases: time-reversal symmetry (TRS) breaking in the Majorana conformal field theory (CFT) and the absence of conformal symmetry in …


Answer Similarity Grouping And Diversification In Question Answering Systems, Lakshmi Nair Vikraman Oct 2022

Answer Similarity Grouping And Diversification In Question Answering Systems, Lakshmi Nair Vikraman

Doctoral Dissertations

The rise in popularity of mobile and voice search has led to a shift in IR from document to passage retrieval for non-factoid questions. Various datasets such as MSMarco, as well as efficient retrieval models have been developed to identify single best answer passages for this task. However, such models do not specifically address questions which could have multiple or alternative answers. In this dissertation, we focus on this new research area that involves studying answer passage relationships and how this could be applied to passage retrieval tasks.

We first create a high quality dataset for the answer passage similarity …


Approximate Bayesian Deep Learning For Resource-Constrained Environments, Meet Prakash Vadera Oct 2022

Approximate Bayesian Deep Learning For Resource-Constrained Environments, Meet Prakash Vadera

Doctoral Dissertations

Deep learning models have shown promising results in areas including computer vision, natural language processing, speech recognition, and more. However, existing point estimation-based training methods for these models may result in predictive uncertainties that are not well calibrated, including the occurrence of confident errors. Approximate Bayesian inference methods can help address these issues in a principled way by accounting for uncertainty in model parameters. However, these methods are computationally expensive both when computing approximations to the parameter posterior and when using an approximate parameter posterior to make predictions. They can also require significantly more storage than point-estimated models.

In this …


How Do Galaxies Form Their Stars Over Cosmic Time?, Jed H. Mckinney Oct 2022

How Do Galaxies Form Their Stars Over Cosmic Time?, Jed H. Mckinney

Doctoral Dissertations

Galaxies in the past were forming more stars than those today, but the driving force behind this increase in activity remains uncertain. In this thesis I explore the origin of high star-formation rates today and in the past by studying the properties of gas and dust in the cold interstellar medium (ISM) of dusty galaxies over cosmic time. Critically, we do not yet understand how these galaxies could form so many stars. This work began with my discovery of unusual infrared (IR) emission line ratios in the class of dusty galaxies where most of the Universe’s stars were formed. To …


Bayesian Hierarchical Temporal Modeling And Targeted Learning With Application To Reproductive Health, Herbert P. Susmann Oct 2022

Bayesian Hierarchical Temporal Modeling And Targeted Learning With Application To Reproductive Health, Herbert P. Susmann

Doctoral Dissertations

The international community via the United Nations Sustainable Development Goals has set the target of universal access to reproductive health-care services, including family planning, by 2030. Progress towards reaching this goal is assessed by tracking appropriate demographic and health indicators at national and subnational levels. This task is challenging, however, in populations where relevant data are limited or of low quality. Statistical models are then needed to estimate and project demographic and health indicators in populations based on the available data. Our first contribution, in Chapter 1, is to unify many existing demographic and health indicator models by proposing an …


Intracellular Delivery Of Therapeutic Biomolecules Through Versatile Polymer Nanotechnology, David C. Luther Oct 2022

Intracellular Delivery Of Therapeutic Biomolecules Through Versatile Polymer Nanotechnology, David C. Luther

Doctoral Dissertations

Advancing pharmaceutical technology has made it possible to treat diseases once considered ‘undruggable.’ Access to these new pharmaceutical targets is possible thanks to the advent of protein and nucleic acid therapeutics. Responses to the COVID-19 pandemic, as well as cutting-edge treatments for cancer and multiple sclerosis have centered on these biologic therapies, promising even greater value in the future. However, their utility is limited at a cellular level by inability to cross the plasma membrane. Nanocarrier technologies encapsulate therapeutics and facilitate uptake into the cell but are often trapped and degraded in endosomes. Arginine-functionalized gold nanoparticles (Arg-NPs) provide efficient, direct …


Controllable Neural Synthesis For Natural Images And Vector Art, Difan Liu Oct 2022

Controllable Neural Synthesis For Natural Images And Vector Art, Difan Liu

Doctoral Dissertations

Neural image synthesis approaches have become increasingly popular over the last years due to their ability to generate photorealistic images useful for several applications, such as digital entertainment, mixed reality, synthetic dataset creation, computer art, to name a few. Despite the progress over the last years, current approaches lack two important aspects: (a) they often fail to capture long-range interactions in the image, and as a result, they fail to generate scenes with complex dependencies between their different objects or parts. (b) they often ignore the underlying 3D geometry of the shape/scene in the image, and as a result, they …


Probabilistic Commonsense Knowledge, Xiang Li Oct 2022

Probabilistic Commonsense Knowledge, Xiang Li

Doctoral Dissertations

Commonsense knowledge is critical to achieving artificial general intelligence. This shared common background knowledge is implicit in all human communication, facilitating efficient information exchange and understanding. But commonsense research is hampered by its immense quantity of knowledge because an explicit categorization is impossible. Furthermore, a plumber could repair a sink in a kitchen or a bathroom, indicating that common sense reveals a probable assumption rather than a definitive answer. To align with these properties of commonsense fundamentally, we want to not only model but also evaluate such knowledge human-like using abstractions and probabilistic principles. Traditional combinatorial probabilistic models, e.g., probabilistic …


Languages And Compilers For Writing Efficient High-Performance Computing Applications, Abhinav Jangda Oct 2022

Languages And Compilers For Writing Efficient High-Performance Computing Applications, Abhinav Jangda

Doctoral Dissertations

Many everyday applications, such as web search, speech recognition, and weather prediction, are executed on high-performance systems containing thousands of Central Processing Units (CPUs) and Graphics Processing Units (GPUs). These applications can be written in either low-level programming languages, such as NVIDIA CUDA, or domain specific languages, like Halide for image processing and PyTorch for machine learning programs. Despite the popularity of these languages, there are several challenges that programmers face when developing efficient high-performance computing applications. First, since every hardware support a different low-level programming model, to utilize new hardware programmers need to rewrite their applications in another programming …


Hyperspectral Unmixing: A Theoretical Aspect And Applications To Crism Data Processing, Yuki Itoh Oct 2022

Hyperspectral Unmixing: A Theoretical Aspect And Applications To Crism Data Processing, Yuki Itoh

Doctoral Dissertations

Hyperspectral imaging has been deployed in earth and planetary remote sensing, and has contributed the development of new methods for monitoring the earth environment and new discoveries in planetary science. It has given scientists and engineers a new way to observe the surface of earth and planetary bodies by measuring the spectroscopic spectrum at a pixel scale.

Hyperspectal images require complex processing before practical use. One of the important goals of hyperspectral imaging is to obtain the images of reflectance spectrum. A raw image obtained by hyperspectral remote sensing usually undergoes conversion to a physical quantity representing the intensity of …