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Design, Synthesis, And Characterization Of Complex Chalcogenides For Energy Storage And Energy Conversion Applications, Srikanth Balijapelly Jan 2024

Design, Synthesis, And Characterization Of Complex Chalcogenides For Energy Storage And Energy Conversion Applications, Srikanth Balijapelly

Doctoral Dissertations

"Through this investigation, complex chalcogenides with the combination of main group metals, transition metals, and rare earth metals have been synthesized using the building block approach and their structure-property relationships are evaluated. The main emphasis of research is on rationally designing new materials for applications in sodium and lithium ion conducting solid electrolytes, cathodes, thermoelectrics, and nonlinear optics. Along with the experimental studies, theoretical calculations are also employed to better understand the physicochemical properties of the synthesized compounds.

The first part of the research will discuss designing alkali ion containing complex chalcogenides using the building block approach. This investigation resulted …


Re-Evaluating Missouri’S Strategic Element Potential: A Geochemical Study Of The Mesoproterozoic Fe-Cu-Co-Ree Deposits In Southeast Missouri, Usa, Brandon James Sullivan Jan 2024

Re-Evaluating Missouri’S Strategic Element Potential: A Geochemical Study Of The Mesoproterozoic Fe-Cu-Co-Ree Deposits In Southeast Missouri, Usa, Brandon James Sullivan

Doctoral Dissertations

"Iron-oxide-copper-gold (IOCG) deposits are poorly understood mineral systems. For example, we do not know why Cu- and Co-rich IOCG deposits typically occur proximal to Fe ore deposits that are notably Cu and Co-poor, such as Iron Oxide Apatite (IOA) deposits. To better understand the formation of IOA and IOCG deposits in Missouri, USA, this PhD thesis examines the genesis of the Kratz Spring IOA and the Boss Central Dome IOCG deposits. This study presents the first constraints on formation conditions and fluid sources in the studied deposits using integrated petrographic, mineral composition, and Fe isotope analyses of oxide minerals. Observations …


The Science Of Gravitational-Wave Sources And Beyond Compact Binary Coalescences, Yanyan Zheng Jan 2024

The Science Of Gravitational-Wave Sources And Beyond Compact Binary Coalescences, Yanyan Zheng

Doctoral Dissertations

"This work focuses on the field of gravitational-wave astronomy by extending the scope of detectable sources beyond compact binary coalescences, All the gravitational-wave detections so far come from compact binary coalescences. Focusing on core-collapse supernovae as promising sources for short gravitational-wave transients, this work reports optically targeted searches for gravitational-wave emitted by core-collapse supernovae during the third observing run of the LIGO and Virgo detectors. It also predicts the search sensitivity for the ongoing fourth and forthcoming fifth observing runs. Moreover, the work introduces a novel computational framework for testing the spatial distribution of binary black hole sources, allowing for …


Experimental Investigation Of High-Temperature Brine-Shale Interactions, Anna Atasha Hoffmann Jan 2024

Experimental Investigation Of High-Temperature Brine-Shale Interactions, Anna Atasha Hoffmann

Doctoral Dissertations

"Hydrofracturing (fracking), a common practice in the Petroleum Industry to induce or improve fluid flow in tight formations, creates chemical disequilibrium that further alters the porosity and permeability of host rocks and results in the production of saline and contaminated produced waters (PW). The PW of the Tuscaloosa Marine Shale (TMS) are Na-Ca-Mg-K-Cl brines with mean concentrations of approximately 16% Total Dissolved Solids (TDS) and circumneutral pH. Analysis of composition suggests the PW result from a 20 to 80% dilution of formation waters (relict brines of the Louann Salt) by fracking fluid. Trace element concentrations generally show moderate to strong …


Synthesis And Characterization Of Quantum Materials, Yunsheng Qiu Jan 2024

Synthesis And Characterization Of Quantum Materials, Yunsheng Qiu

Doctoral Dissertations

"In this study, attempts were made to grow quantum materials that have recently undergone a profound change of perspective. These materials are involved in intricate macroscopic properties rooted in the subtle nature of quantum physics. To explore our understanding of quantum materials, this study includes three projects: Magnetic Topological Insulators, Topological Superconductors, and high-temperature superconductors.

A Cr-doped Sb2Te3 is added to the category for the magnetic topological insulators project. Their transport properties are studied, and the origin of ferromagnetism is studied. Anomalous Hall effect is observed in the Hall measurements, and serval factors (cooling rate, dopant deficiency) …


Chirality Determination Using Three-Wave Mixing Microwave Spectroscopy, Nicole Taylor Moon Jan 2024

Chirality Determination Using Three-Wave Mixing Microwave Spectroscopy, Nicole Taylor Moon

Doctoral Dissertations

"Rotational spectroscopy has established itself as a reliable gas-phase spectroscopic technique for the structural determination of molecules. This reliability has stemmed from both advancements in microwave technology and a willingness from the community to push the boundaries of the field. In this dissertation, the boundaries are tested in both how well the technique can determine the structure of molecules exhibiting large amplitude motion and through chirality determination. The first half of this dissertation explores the use of deep averaging to determine the structure of silicon containing molecules in collaboration with Dr. Guirgis from the College of Charleston. For each of …


The Deep Bsde Method, Daniel Kovach Jan 2024

The Deep Bsde Method, Daniel Kovach

Masters Theses

"The curse of dimensionality is the non-linear growth in computing time as the dimension of a problem increases. Using the Deep Backwards Stochastic Differential Equation (Deep BSDE) method developed in [HJE18], I approximate the solution at an initial time to a one-dimensional diffusion equation. Although we only approximate a one-dimensional equation, this method extends well to higher dimensions because it overcomes the curse of dimensionality by evaluating the given partial differential equation along "random characteristics''. In addition to the implementation, I also present most of the mathematical theory needed to understand this method"-- Abstract, p. iii


Time Series Anomaly Detection Using Generative Adversarial Networks, Shyam Sundar Saravanan Jan 2024

Time Series Anomaly Detection Using Generative Adversarial Networks, Shyam Sundar Saravanan

Masters Theses

"Anomaly detection is widely used in network intrusion detection, autonomous driving, medical diagnosis, credit card frauds, etc. However, several key challenges remain open, such as lack of ground truth labels, presence of complex temporal patterns, and generalizing over different datasets. In this work, we propose TSI-GAN, an unsupervised anomaly detection model for time-series that can learn complex temporal patterns automatically and generalize well, i.e., no need for choosing dataset-specific parameters, making statistical assumptions about underlying data, or changing model architectures. To achieve these goals, we convert each input time-series into a sequence of 2D images using two encoding techniques with …


A New Proper Orthogonal Decomposition Method With Second Difference Quotients For The Wave Equation, Andrew Calvin Janes Jan 2024

A New Proper Orthogonal Decomposition Method With Second Difference Quotients For The Wave Equation, Andrew Calvin Janes

Masters Theses

"Recently, researchers have investigated the relationship between proper orthogonal decomposition (POD), difference quotients (DQs), and pointwise in time error bounds for POD reduced order models of partial differential equations. In \cite {Sarahs}, a new approach to POD with DQs was developed that is more computationally efficient than the standard DQ POD approach and it also retains the guaranteed pointwise in time error bounds of the standard method. In this thesis, we extend the new DQ POD approach from \cite {Sarahs} to the case of second difference quotients (DDQs). Specifically, a new POD method utilizing DDQs and only one snapshot and …


Hysplit In Simulating The Atmospheric Dispersion Of Hazardous Aerosols: A Case Study In St. Louis, Missouri, Ahmet Tolga Odabasi Jan 2024

Hysplit In Simulating The Atmospheric Dispersion Of Hazardous Aerosols: A Case Study In St. Louis, Missouri, Ahmet Tolga Odabasi

Masters Theses

"Atmospheric dispersion and transmission play an important role in the behavior and effects of air pollution. Human health can be adversely affected by air pollution in a variety of ways, both immediately and over time. The Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) modeling program, a computer model and software package, tracks the transport trajectories and distributions of air pollution and various pollutants, including radioactive pollutants, in the atmosphere. It also facilitates research on pollution sources. This study simulated the transport of hazardous aerosols in St. Louis region for the years 2020, 2021, and 2022 using the HYSPLIT modeling …


Meta-Analysis Of Mesenchymal Stem Cell Gene Expression Data From Obese And Non-Obese Patients, Dakota William Shields Jan 2023

Meta-Analysis Of Mesenchymal Stem Cell Gene Expression Data From Obese And Non-Obese Patients, Dakota William Shields

Masters Theses

"The prevalence of gene expression microarray datasets in public repositories gives opportunity to analyze biologically interesting datasets without running the laboratory aspect in house. Such experimentation is expensive in terms of finances, time, and expertise, which often results in low numbers of replicates. Meta-analysis techniques attempt to overcome issues due to few biological or technical replicates by combining separate experiments together to increase statistical power. Proper statistical considerations help to offset issues like simultaneous testing of thousands of genes, unintended hybridization, and other noises.

Microarrays contain light intensities from tens of thousands of hybridized probes giving a measure of gene …


Dynamic Discounted Satisficing Based Driver Decision Prediction In Sequential Taxi Requests, Sree Pooja Akula Jan 2023

Dynamic Discounted Satisficing Based Driver Decision Prediction In Sequential Taxi Requests, Sree Pooja Akula

Masters Theses

"Ridesharing platforms rely on connecting available taxi drivers to potential passengers to maximize their revenue. However, predicting the stopping decision made by every driver, i.e., the final task performed during a given day, is crucial to achieving this goal. Unfortunately, little research has been done on predicting drivers’ stopping decisions, especially when they deviate from expected utility maximization behavior. This research proposes a Dynamic Discounted Satisficing (DDS) heuristic to model and learn the task at which human agents will stop working for that day, assuming that the human agents are taking sequential decisions based on their preference order. We apply …


Electrodeposition Of Epitaxial Wide Bandgap P-Type Semiconductors And Copper Metal For Energy Conversion And Flexible Electronics, Bin Luo Jan 2023

Electrodeposition Of Epitaxial Wide Bandgap P-Type Semiconductors And Copper Metal For Energy Conversion And Flexible Electronics, Bin Luo

Doctoral Dissertations

"Epitaxial electrodeposition is a simple, low-cost technology to produce highly ordered materials on single-crystal surfaces. This research focuses on the epitaxial electrodeposition of wide bandgap p-type semiconductors and epitaxial Cu thin films via a self-assembled monolayer for energy conversion and flexible electronics. Paper I introduces the epitaxial electrodeposition of hole conducting CuSCN nanorods onto Au (111) surface, and lift-off to produce flexible and transparent foils. Highly ordered CuSCN could serve as an inorganic transport layer in various opto-electronic devices such as perovskite solar cells, LEDs, and transistors. An ordered and transparent CuSCN foil was also produced by epitaxial lift-off following …


Novel Quantum Materials For Spintronic And Opto-Electronic Applications, Ali Sarikhani Jan 2023

Novel Quantum Materials For Spintronic And Opto-Electronic Applications, Ali Sarikhani

Doctoral Dissertations

"Multi-functional quantum materials play a crucial role in the development of spintronics and opto-electronics, as their properties can greatly influence device performance. For instance, in spintronics, materials such as ferromagnetic half-metals, Giant Magnetoresistants (GMR), and magnetic semiconductors have been extensively studied due to their ability to manipulate the spin of electrons for applications in magnetic storage. In opto-electronics, materials such as Diluted Magnetic Semiconductors (DMS) and non-oxide Transparent Conductors (TC) offer advantages such as tunable bandgap and high absorption coefficients, which enable improved device performance.

For this purpose, we have experimentally investigated the compounds that have shown theoretically interesting physical …


Efficient High Order Ensemble For Fluid Flow, John Carter Jan 2023

Efficient High Order Ensemble For Fluid Flow, John Carter

Doctoral Dissertations

"This thesis proposes efficient ensemble-based algorithms for solving the full and reduced Magnetohydrodynamics (MHD) equations. The proposed ensemble methods require solving only one linear system with multiple right-hand sides for different realizations, reducing computational cost and simulation time. Four algorithms utilize a Generalized Positive Auxiliary Variable (GPAV) approach and are demonstrated to be second-order accurate and unconditionally stable with respect to the system energy through comprehensive stability analyses and error tests. Two algorithms make use of Artificial Compressibility (AC) to update pressure and a solenoidal constraint for the magnetic field. Numerical simulations are provided to illustrate theoretical results and demonstrate …


Advances In Differentially Methylated Region Detection And Cure Survival Models, Daniel Ahmed Alhassan Jan 2023

Advances In Differentially Methylated Region Detection And Cure Survival Models, Daniel Ahmed Alhassan

Doctoral Dissertations

"This dissertation focuses on two areas of statistics: DNA methylation and survival analysis. The first part of the dissertation pertains to the detection of differentially methylated regions in the human genome. The varying distribution of gaps between succeeding genomic locations, which are represented on the microarray used to quantify methylation, makes it challenging to identify regions that have differential methylation. This emphasizes the need to properly account for the correlation in methylation shared by nearby locations within a specific genomic distance. In this work, a normalized kernel-weighted statistic is proposed to obtain an optimal amount of "information" from neighboring locations …


Essays On Conditional Heteroscedastic Time Series Models With Asymmetry, Long Memory, And Structural Changes, K C M R Anjana Bandara Yatawara Jan 2023

Essays On Conditional Heteroscedastic Time Series Models With Asymmetry, Long Memory, And Structural Changes, K C M R Anjana Bandara Yatawara

Doctoral Dissertations

"The volatility of asset returns is usually time-varying, necessitating the introduction of models with a conditional heteroskedastic variance structure. In this dissertation, several existing formulations, motivated by the Generalized Autoregressive Conditional Heteroskedastic (GARCH) type models, are further generalized to accommodate more dynamic features of asset returns such as asymmetry, long memory, and structural breaks. First, we introduce a hybrid structure that combines short-memory asymmetric Glosten, Jagannathan, and Runkle (GJR) formulation and the long-memory fractionally integrated GARCH (FIGARCH) process for modeling financial volatility. This formulation not only can model volatility clusters and capture asymmetry but also considers the characteristic of long …


Near-Ir Spectroscopic Analysis Of The Primary Volatile Composition Of Long And Short-Period Comets, Younas Khan Jan 2023

Near-Ir Spectroscopic Analysis Of The Primary Volatile Composition Of Long And Short-Period Comets, Younas Khan

Doctoral Dissertations

"Comets are among the most well-preserved objects that formed in the protosolar nebula ∼4.5 Gyr ago. Hence, they are important for understanding various aspects of the formation, evolution, and habitability of the solar system. Multiple primary volatiles (molecules directly sublimating into the coma from the nucleus) emit via rovibrational transitions in the near-IR, providing opportunities to calculate their abundances. To date, only ∼50 comets have been characterized for their primary volatiles, with the short-period Jupiter-family comets (JFCs) being significantly underrepresented. In contrast, hundreds of comets have been sampled at optical/UV wavelengths, primarily for the composition of daughter species, leading to …


Fluorination Of Rubisco-Mimetic Co2 Capture Systems. Theoretical And Experimental Studies Of Ammonium Ion Acidity Depression And Carbamylation, Brian Michael Jameson Jan 2023

Fluorination Of Rubisco-Mimetic Co2 Capture Systems. Theoretical And Experimental Studies Of Ammonium Ion Acidity Depression And Carbamylation, Brian Michael Jameson

Doctoral Dissertations

"RuBisCO-inspired CO2 capture and release (CCR) systems featuring amines have been developed for the purpose of reversable CO2 capture from air. The enzyme active site consists of the tetrapeptide sequence Lys-Asp-Asp-Glu. The Lys sidechain amine undergoes carbamylation and an Mg2+ cation stabilizes the resulting carbamate. The Na-acyl-lysinyl-aspratyl-aspartyl-glutamide (Lys-Asp-Asp-Glu, KDDE) peptide featured maximum capture at pH ≈ 10; a pH region too high for Mg2+ ions to remain in solution. This work aims to achieve pKa depression by introducing fluorine in the proximity of the lysine’s sidechain amine. A comparative analysis was made of butylamine, …


Recurrent Event Data Analysis With Mismeasured Covariates, Ravinath Alahakoon Mudiyanselage Jan 2023

Recurrent Event Data Analysis With Mismeasured Covariates, Ravinath Alahakoon Mudiyanselage

Doctoral Dissertations

"Consider a study with n units wherein every unit is monitored for the occurrence of an event that can recur with random end of monitoring. At each recurrence, p concomitant variables associated to the event recurrence are recorded with q (q ≤ p) collected with errors. Of interest in this dissertation is the estimation of the regression parameters of event time regression models accounting for the covariates. To circumvent the problem of bias and consistency associated with model's parameter estimation in the presence of measurement errors, we propose inference for corrected estimating functions with well-behaved roots under additive measurement errors …


Applied Geochemistry, Geochronology And Biostratigraphy: Case Studies From The 38th Parallel Structures In Missouri And Orange Basin, Offshore Western South Africa, Marissa Kay Spencer Jan 2023

Applied Geochemistry, Geochronology And Biostratigraphy: Case Studies From The 38th Parallel Structures In Missouri And Orange Basin, Offshore Western South Africa, Marissa Kay Spencer

Doctoral Dissertations

"The unique alignment of the Decaturville, Crooked Creek, and Weaubleau geological structures in central Missouri, three of nine known such structures along the 38th parallel in Illinois, Missouri, and Kansas, has puzzled geoscientists for decades. Research using palynology (palynomorphs and particulate organic matter) and radiometric dating of impact spherules were used to constrain age and a relationship between these enigmatic structures and infer their paleoenvironmental conditions. Novel melting damages, unique to impact, were documented in the palynomorphs in all the three structures. Early Ordovician acritarchs with melted processes correlate with 40Ar-39Ar stepwise heating age of impact spherules …


The Application Of Statistical Modeling To Identify Genetic Associations With Mild Traumatic Brain Injury Outcomes, Caroline Schott Jan 2023

The Application Of Statistical Modeling To Identify Genetic Associations With Mild Traumatic Brain Injury Outcomes, Caroline Schott

Masters Theses

"Traumatic brain injury (TBI) is a growing health concern, with millions of TBI diagnoses in the United States each year. The vast majority of TBI diagnoses are mild traumatic brain injuries (mTBI), which can be challenging to manage due to variation in symptoms and outcomes. Most individuals with mTBI successfully recover quickly, but a small subset has a delayed recovery. Although the factors that contribute to this variation in recovery are not clearly understood, it is possible that genetic differences may play a role. Very few studies have investigated the association between single nucleotide polymorphisms (SNPs) with mTBI outcomes and …


Computer Vision In Adverse Conditions: Small Objects, Low-Resoltuion Images, And Edge Deployment, Raja Sunkara Jan 2023

Computer Vision In Adverse Conditions: Small Objects, Low-Resoltuion Images, And Edge Deployment, Raja Sunkara

Masters Theses

"Computer vision based on deep learning is an essential field that plays a significant role in object detection, image classification, semantic segmentation, instance segmentation, and other applications. However, these models face significant challenges in adverse conditions, such as small objects, low-resolution images, and edge deployment. These challenges limit the accuracy and efficiency of computer vision algorithms, making it difficult to obtain reliable results.

The primary objective of this thesis is to assess the performance of deep learning- based computer vision models in challenging conditions and provide viable solutions to overcome the obstacles. The study will specifically address three key challenges, …


Mat: Genetic Algorithms Based Multi-Objective Adversarial Attack On Multi-Task Deep Neural Networks, Nikola Andric Jan 2023

Mat: Genetic Algorithms Based Multi-Objective Adversarial Attack On Multi-Task Deep Neural Networks, Nikola Andric

Masters Theses

"Vulnerability to adversarial attacks is a recognized deficiency of not only deep neural networks (DNNs) but also multi-task deep neural networks (MT-DNNs) that attracted much attention in the past few years. To the best of our knowledge, all multi-task deep neural network adversarial attacks currently present in the literature are non-targeted attacks that use gradient descent to optimize a single loss function generated by aggregating all loss functions into one. On the contrary, targeted attacks are sometimes preferred since they give more control over the attack. Hence, this paper proposes a novel targeted multi-objective adversarial ATtack (MAT) based on genetic …


Investigation Of Defect Production And Displacement Energies In Wurtzite Aluminum Nitride, Sean Anderson Jan 2023

Investigation Of Defect Production And Displacement Energies In Wurtzite Aluminum Nitride, Sean Anderson

Masters Theses

"Aluminum Nitride is an active element of sensors that monitor the performance and well-being of the nuclear reactors due to its piezoelectric properties. Yet, the variations of its properties under irradiation are largely unexplored. We report the results of the molecular dynamics simulations of the structural changes in AlN under irradiation via the knock-on atom technique. By creating and evolving the irradiation cascades due to energetic particle interaction with the atom of the crystalline lattice we determine the rate of the defect production as a function of the deposited energy. Further, we determine a displacement energy, a key characteristic that …


Secured Information Dissemination And Misbehavior Detection In Vanets, Ayan Roy Aug 2022

Secured Information Dissemination And Misbehavior Detection In Vanets, Ayan Roy

Doctoral Dissertations

"In a connected vehicle environment, the vehicles in a region can form a distributed network (Vehicular Ad-hoc Network or VANETs) where they can share traffic-related information such as congestion or no-congestion with other vehicles within its proximity, or with a centralized entity via. the roadside units (RSUs). However, false or fabricated information injected by an attacker (or a malicious vehicle) within the network can disrupt the decision-making process of surrounding vehicles or any traffic-monitoring system. Since in VANETs the size of the distributed network constituting the vehicles can be small, it is not difficult for an attacker to propagate an …


Social Media Analytics With Applications In Disaster Management And Covid-19 Events, Md Yasin Kabir Aug 2022

Social Media Analytics With Applications In Disaster Management And Covid-19 Events, Md Yasin Kabir

Doctoral Dissertations

"Social media such as Twitter offers a tremendous amount of data throughout an event or a disastrous situation. Leveraging social media data during a disaster is beneficial for effective and efficient disaster management. Information extraction, trend identification, and determining public reactions might help in the future disaster or even avert such an event. However, during a disaster situation, a robust system is required that can be deployed faster and process relevant information with satisfactory performance in real-time. This work outlines the research contributions toward developing such an effective system for disaster management, where it is paramount to develop automated machine-enabled …


Using Coherence And Interference To Study The Few Body Dynamics In Simple Atomic Collisions Systems, Sujan Bastola Aug 2022

Using Coherence And Interference To Study The Few Body Dynamics In Simple Atomic Collisions Systems, Sujan Bastola

Doctoral Dissertations

"Atomic Collision experiments are best suited to sensitively test the few-body dynamics of simple systems. The few-body dynamics, in turn, can be sensitively affected by interference effects. However, an important requirement to observe interference effects in atomic scattering experiments is that the incoming projectile beam must be coherent. The coherence properties of the incoming projectile can be controlled by the geometry of the collimating slit placed before the target. We performed a kinematically complete experiment where a 75 keV proton beam is crossed with a molecular hydrogen beam to study the dissociative capture process. The motivation for this project was …


Survivor Bond Models For Securitizing Longevity Risk, Priscilla Mansah Codjoe Aug 2022

Survivor Bond Models For Securitizing Longevity Risk, Priscilla Mansah Codjoe

Doctoral Dissertations

"Longevity risk is the risk that a reference population’s mortality rates deviate from what is projected from prior life tables. This is due to discoveries in biological sciences, improved public health measures, and nutrition, which have dramatically increased life expectancy. Longevity risk raises life insurers’ liability, increasing product costs and reserves. Securitization through longevity derivatives is a way of dealing with this risk.

To enhance the pricing of life contingent products, we present an additive type mortality model in the style of the Lee-Carter. This model incorporates policyholder covariates. By using counting processes and martingale machinery, we obtain close form …


Hydroclimate Variability In Central America During The Holocene Inferred From Lacustrine Sediments In Lake Izabal, Eastern Guatemala, Edward Fernando Duarte Aug 2022

Hydroclimate Variability In Central America During The Holocene Inferred From Lacustrine Sediments In Lake Izabal, Eastern Guatemala, Edward Fernando Duarte

Doctoral Dissertations

"Holocene hydroclimate reconstructions have contributed to our understanding of the mechanisms controlling precipitation in Central America. Recent hydroclimate proxy records from the region, however, have revealed considerable spatiotemporal complexity in precipitation variability. This complexity is hypothesized to result from the interaction between multiple oceanic-atmospheric processes that converge in the region. This project analyzed three sediment cores from Lake Izabal, eastern lowland Guatemala, with the goal of understanding changes in precipitation, lake productivity, and lake water chemistry during the Holocene. Our proxy results indicate that precipitation in the region increased from the early to the middle Holocene, when Lake Izabal became …