Digital Commons Network^™

Design And Synthesis Of Organocatalyts For Efficient Decontamination Of Organophosphate-Based Nerve Agents And Pesticides, Emmanuel Kingsley Darkwah

Doctoral Dissertations

Exposure to organophosphate-based nerve agents and pesticides poses significant health and security threats to civilians, soldiers, and first responders. Despite extensive efforts to develop chemical detoxification agents for use in topical applications on exposed skin surfaces and for intravenous injections, there remains an unmet need for effective, non-hazardous decontaminating agents. The current state-of-the-art decontaminating agent, Dekon-139 (2,3-butanedione oxime, potassium salt), exhibits adverse effects when applied to the skin.

In this study, we designed and synthesized pharmaceutically relevant aminoguanidine-derived aldimines that are relatively non-toxic and substantially more effective at decontaminating nerve agents and pesticides compared to existing agents, and they act …

Epitaxial Growth Of Metal-Organic Framwork Thin Films By Electro-Conversion And Electrodeposition, Xiaoting Zhang

Doctoral Dissertations

Electrochemical epitaxy is a facile and inexpensive soft-solution process to fabricate highly ordered thin films. This research focuses on the epitaxial growth of metal-organic framework (MOF) thin films by electrochemical methods which include electro-conversion and electrodeposition.

First, an electrochemical conversion pathway was invented to achieve epitaxial MOF thin films. Epitaxial single-domain Cu-BTC(111) thin films were manufactured by electrochemical oxidation of Cu₂O(111) films electrodeposited on single-crystal Au(111). The single-crystal-like Cu-BTC(111) thin films with out-of-plane and in-plane order provide well-aligned 3.5 Å triangular windows along the [111] direction. Cu-BTC(111) foils were fabricated from the Cu-BTC/Cu₂O system by electrochemical …

Enhanced Optimization Of Mass Transfer For Carbon Capture And Wastewater Remediation In Algal Systems Through Algorithmic And Bioprocessing Techniques, Peter Ofuje Obidi

Doctoral Dissertations

The scalability and industrial deployment of algal cultivation systems are limited by suboptimal mass transfer, constraining their effectiveness in carbon capture and wastewater remediation. This research investigated these challenges through integrated optimization methodologies that combine algorithmic frameworks with enhanced bioprocessing techniques to enhance efficiency, economy, and scalability. A System-of-Systems (SoS) meta-architecture was developed using genetic algorithms and fuzzy assessor functions to demonstrate a pathway toward cost reduction. Rigorous mechanical and chemical characterizations were quantitatively analyzed to reveal existing optimization strategies and further evaluated the best strategies to use in enhancing mass transfer for improved biomass yield. The work also integrates …

Supporting Human-Ai Interaction From User Expectations To Mental Models, Harishankar Vasudevanallur Subramanian

Doctoral Dissertations

Explainable AI (XAI) aims to unravel the "black box" nature of AI systems and provide insights into the inner workings that lead to a prediction. However, the best XAI communication varies depending on the individual, task, and broader context. It is challenging to anticipate the best XAI for a particular use case. One strategy is for users to build an appropriate mental model of AI with both prediction and system level XAI. To date, little research has focused on quantitatively measuring users interacting with system-level XAI. This dissertation has three primary contributions. The first contribution is a scoping review paper …

Higher-Order Statistics And Normalized Decay Analysis For Detector Deadtime Characterization, Abdallah Wazzan

Doctoral Dissertations

Detector deadtime limits radiation measurement accuracy at high count rates, yet current methods rely on idealized paralyzable or non-paralyzable models. Real detectors exhibit hybrid behavior requiring advanced characterization approaches. This study explores deadtime characterization using two Monte Carlo simulation approaches: higher-order statistical analysis of inter-arrival times and simplified deadtime correction with hybrid models.

Using MATLAB (PULSE-WIZ), we analyzed full decay curves spanning ~4.5 half-lives of Cobalt-60 and Vanadium-52, examining coefficient of variation (CV), skewness, and kurtosis of inter-arrival times, plus normalized decay curves with Full Width at Half Maximum (FWHM) analysis. Hybrid models incorporated paralyzable and non-paralyzable components with dead …

Introducing Triangular Groups And Further Results On Magic Groups, Nicholas Charles Fleece

Doctoral Dissertations

In this research, we discuss two new topics in group theory. First, we define an n-magic square in a group to be a nxn array of group elements whose rows, columns, and diagonals have the same product. This definition is akin to the idea of magic squares in the integers. Groups that have an n-magic square are said to be n-magic. We begin with some preliminary results and focus much of our attention on 3-magic groups, though we also give some results for higher n. Through a series of propositions, we ultimately prove a characterization theorem for 3-magic finitely generated …

Products Of Laser Ablated Actinides And Actinide Comparators In The Presence Of Carbonyl Sulfide Characterized By Rotational Spectroscopy, Joshua Edward Isert

Doctoral Dissertations

As the consumption of energy continues to rise globally, so too has interest in alternative energy sources such as nuclear power. However, a fundamental understanding of the actinide series is needed in order to safely and efficiently utilize these elements. Rotational or microwave spectroscopy, depending on if one is speaking of the physical outcome of the experiment or the region of the electromagnetic spectrum being operated in, is a gas phase molecular study utilized for structural determination. This technique can be utilized to gain an in depth understanding of bonding within the actinide series. However, when studying species that are …

Tailoring Selected Aerogels To Targeted Applications, Stephen Yaw Owusu

Doctoral Dissertations

Aerogels are ultra-lightweight, porous solid materials characterized by a three-dimensional nanostructured network. Owing to their exceptional physical and chemical properties, aerogels have garnered considerable attention within the materials science community and were recognized by IUPAC in 2022 as one of the top ten emerging technologies in chemistry. Although numerous aerogels have been synthesized, only a few have been effectively tailored for specific applications. Optimizing the properties of known aerogels for targeted uses remains challenging. This dissertation investigates strategies for tailoring aerogels derived from isocyanate-benzoxazine, benzodiazine, and phenolic resins to meet the requirements of various advanced applications. The approaches employed include …

Machine Learning Models For Location Prediction, Message Routing And Path Planning For Rescue Of Underground Miners, Abhay Goyal

Doctoral Dissertations

Self-rescue during underground mine disasters is vital for miner safety. Evolving hazards and post-disaster conditions demand solutions that enable navigation under severe communication and computational constraints. Centralized systems often fail in such rugged settings, while decentralized methods—particularly Delay Tolerant Networks (DTNs), proven in battlefields and space missions—offer distinct advantages for underground applications. This research addresses five core challenges: (i) predicting miners’ next locations on low-power devices using points of interest and movement sequences; (ii) delivering timely updates on safe routes, evacuation zones, and hazardous areas; (iii) evaluating energy efficiency and comparing graph-based approaches to existing methods; (iv) enabling edge-ready frameworks, …

Radio Frequency Wave Propagation Modeling Within Obstructed Underground Mining Environments For Effective Miner Localization During Mine Emergencies, Emmanuel Atta Antwi

Doctoral Dissertations

The reliability of underground wireless communication systems remains a significant challenge, particularly during emergencies when the mine environment becomes severely obstructed by debris, dust, and humidity. These environmental and geometric conditions result in significant attenuation of electromagnetic (EM) waves and multipath effects that undermine miner localization and rescue operations. Existing Vector Parabolic Equation (VPE) models are efficient for straight or mildly curved tunnels but fail to account for the random and obstructive conditions typically encountered during underground emergencies. This research develops a novel radio propagation model for EM wave behavior in underground mine drifts under geometrically obstructed conditions. The model …

Generalizations Of Finiteness Conditions And Extension Monads In Algebras With Infinitely Many Or Infinitary Operations, Danielle Christienne Bowerman

Doctoral Dissertations

In this work, we extend the results of finiteness conditions and extension monads found in Insall from finitely many finitary operations to infinitely many finitary operations, as well as touching on infinitary operations. We also examine varieties of algebras, including the notion of strong varieties introduced in Insall, and common constructions of extension monads in varieties of algebras. We see that for finite collections of algebras of the same signature, the extension monad operation on a variety of algebras commutes with the direct product operation, and all retractions from an enlargement or extension monad are trivial. We also see that …

Optical Sensor Instrumentation For Enhanced Continuous Caster Development, Hanok Wondimagegnehu Tekle

Doctoral Dissertations

Fiber-optic sensors are an emerging technology that can enhance process monitoring and control in steelmaking. They are especially valuable in the continuous caster’s harsh environment. This dissertation presents the industrial application and demonstration of three sensor types: single-mode silica fiber with Rayleigh-based Optical Frequency Domain Reflectometry (OFDR), sapphire fiber (single-crystal alumina) with Fiber Bragg Gratings (sFBG), and an in-line Raman spectroscopy probe. Each sensor served a distinct role in the continuous caster. Rayleigh OFDR sensors were embedded in tundishes for distributed thermal mapping at 7-mm spatial resolution across ≈4 m. Measurements were taken during preheating, casting, and ladle exchanges, and …

Hyper B-Ary Representations Of A Number, Mingway Wang

Masters Theses

In this work, we summarize combinatorial, analytical, and computational properties of Stern's diatomic sequence, and do the same for a generalization of a combinatorial property of this sequence to higher bases. We then construct special ``bit conversion'' functions $g_{b}$ that allows us to find a semi-explicit formula for the generalized sequences. Lastly, we analyze some of the properties of these $g_{b}$ functions.

On Optimizing Sensor Data Collection, Processing, And Storage For Industrial Additive Manufacturing, Steven Thompson

Masters Theses

The widespread adoption of digital data management methods for transformative technologies, such as additive manufacturing (AM), within the aerospace industry is impeded by poor interoperability between AM component manufacturing processes. Moreover, data quality may be compromised due to sensor failures or other corruptions. Additionally, massive amounts of data are collected during these processes, often needing to remain accessible for decades. These storage costs can place a significant financial burden on smaller suppliers. This work aims to make digital data management methods more affordable and, therefore, approachable for smaller suppliers.

First, the design and initial implementation of an affordable and adaptable …

Augmentation Of Quality Of Service, Security, And Trust In Edge-Enhanced Iot Networks Leveraging Blockchain, Kyle Matthew Whitlatch

Masters Theses

The meteoric rise of the Internet of Things (IoT) has led to multiple architectural schemas to handle the data these devices create. Edge-enhancement is a technique where groups of IoT report to a median layer to aggregate the data before relaying to the endpoint. These edges also open opportunities to perform more operations to ensure devices are behaving properly before committing the data to long term storage. By interconnecting these edges with a technology like blockchain, it is possible to have an interconnected and responsive system to ensure the Quality of Service (QoS) of the IoT devices within the architecture …

Development Of A Method To Measure Blast Overpressure Exposure Using Orthogonal Sensor Orientations, Nicholas Kuehl

Masters Theses

Measuring and recording blast exposure to military personnel from shoulder-fired weaponry or improvised explosive devices to correlate health outcomes like mild traumatic brain injury has been a goal for many years. As such, many wearable sensors have been developed and tested for accuracy and reliability. Despite this, knowing the sensor orientation in relation to the blast source is important to fully correlate the actual personnel exposure to clinical outcomes. This research investigates whether pressures recorded at three independent orientations in the x, y and z planes can be combined to a representative pressure that is independent of orientation. Important metrics …

Power Flow Control Of The Triple Active Bridge Converter, Lauryn Reece Morris

Masters Theses

With the rise of renewable energies, electric vehicles, and microgrids, the development of power electronic topologies that can seamlessly integrate these systems into the grid is crucial. The triple active bridge is an extension of the dual active bridge topology and is capable of energy storage or renewable energy integration into a power electronic converter and thus the power grid. Consisting of three H-Bridge converters, the triple active bridge topology is an expanding area of research to meet these growing demands. With the addition of the third bridge, the system has additional nonlinear characteristics which introduce complexity in solving for …

Critical Behavior Ofthedilutedquasi-Onedimensionalquantum Ising Model, Logan Bradley Sowadski

Masters Theses

We explore the phase transition in the diluted quasi-one-dimensional quantum Ising model. We begin by giving an introduction to the Ising model followed by derivations of the properties and observables. A brief overview of Monte-Carlo simulations is also given focusing on two algorithms that make simulations for physically realizable systems possible, the Metropolis and Wolff algorithms. We finally discuss the concept of random disorder in the system and the effects this can have on the bulk of the system.

These concepts are then directly applied to a quasi-one-dimensional Ising model. Motivated by recent experiments on the spin-chain material cobalt niobate, …

Aerodynamic Design Workflow Optimization For Fsae: Advanced Cfd And Hpc Automation, Kyle Maynor

Masters Theses

This research identifies and resolves inefficiencies in the Computational Fluid Dynamics (CFD) workflow of the Missouri S&T Racing Formula SAE Team’s aerodynamic development. Key bottlenecks were found in simulation runtime, laborious simulation preparation, an overly manual simulation submission process, and unchecked mesh quality. A fully reimagined workflow was implemented with simulation parameters to adjust vehicle attitudes. From this, an automated design sweep could be executed to generate aero maps of the developing vehicle using the Design Manager Project. A Python-based submission app handles the terminal interfacing and macro editing that significantly slowed the job submission process before. Using a university …

Development Of Stalling Detection Algorithms And Operator Behavior Models For Evaluating Hydraulic Excavator Performance, Mateo Fernando Montenegro Defaz

Masters Theses

This study aims to develop a reliable algorithm for stalling detection and investigate how operator behaviors impact the truck-loading process, focusing on swing and bucket rotations. While the study of excavator digging conditions and equipment performance is well understood, describing stalling from telemetry data and the influence of operators’ behavior on overall system efficiency remain underexplored. This study seeks to: (i) develop a reliable algorithm for stall detection by analyzing key operational variables such as velocity and angles; (ii) implement statistical and machine learning techniques, specifically a Support Vector Machine (SVM) classification algorithm, to differentiate between ideal and non-ideal digging …

Design Of A Spacecraft Power System Experiment, Jay Bakulkumar Kamdar

Masters Theses

This research delves into the design, implementation, and analysis of a controlled experimental framework for photovoltaic cell characterization and its application in spacecraft power systems. Such a system was simulated and validated by benchmarking characteristics of a photovoltaic module and implementing them in a system design simulation yielding performance data for comparative analysis. A hardware setup was developed to perform IV characterization tests under steady state thermal conditions. Experiments conducted across various thermal regulation profiles helped quantify the effects of temperature on the photovoltaic performance parameters. Active cooling reduced the steady state cell temperature by 17.9% and improved the cell …

Overall Tropospheric Noise Over The St. Louis Using Isce And Fringe Processing, Maryann Lee

Masters Theses

Interferometric Synthetic Aperture Radar (InSAR) is a satellite-based technique that is used to measure various aspects such as ground deformation, earthquakes, volcanic activity, and motions of glaciers. Although the technique has proved very useful, measurements errors such as ionospheric and tropospheric noise, and deformation often cause problems with making precise measurements. InSAR is a tool used in geodesy that is used to measure the change of surface deformation over time through a series of repeated SAR acquisitions. These errors in the acquisitions occur from factors of signal decorrelation, atmospheric delays, and phase unwrapping errors that affect the accuracy and precision …

Evaluating Tropospheric Delay Modeling For Enhanced Geospatial Accuracy, Adeyinka Olaoluwa Olaseinde

Masters Theses

Interferometric Synthetic Aperture Radar (InSAR) is a vital technique for monitoring ground surface deformation across large spatial scales. However, variability in atmospheric water vapor, pressure, and temperature introduces tropospheric delays that can significantly affect measurement accuracy. These delays are often corrected using outputs from numerical weather prediction (NWP) models. RAiDER, an open-source Python package, facilitates this by estimating tropospheric delays using models such as the High-Resolution Rapid Refresh (HRRR). Previous studies have shown that weather model–based corrections can substantially reduce atmospheric noise in InSAR data but also highlight persistent residual errors, especially at spatial scales smaller than the model grid …

Multimodal Spatio-Temporal Pest Prediction In Precision Agriculture, V N S Kameswari Sri Sindhu Manchikanti

Masters Theses

Accurate and timely prediction of pest outbreaks is a cornerstone of Agriculture 5.0, which emphasizes intelligent, data-driven, and sustainable decision-making in crop production. This research presents a multimodal deep learning framework that integrates heterogeneous data sources, including weather parameters, satellite-derived vegetation indices, and static and dynamic soil attributes, to forecast pest population dynamics under varying management and ecological conditions. The proposed framework employs modality-specific deep encoders to capture distinct temporal and spatial representations from each data stream and merges them through a late-fusion architecture that learns cross-modal dependencies critical to pest emergence. The design further incorporates treatment-aware and multiclass extensions, …

Application Of Edge-Enhanced Phase Analysis To Active Microwave Thermographic Measurements, Douglas Blaine Fleetwood

Masters Theses

Nondestructive testing and evaluation (NDT&E) encompasses a range of inspection techniques that assess materials, components, and structures while maintaining their integrity and performance. Among these techniques, thermography is particularly attractive due to its non-contact imaging approach with easy-to-interpret results. Active Microwave Thermography (AMT) has emerged as a promising NDT&E inspection technique that utilizes electromagnetic energy to heat materials through dielectric and magnetic absorption, with subsequent infrared imaging used to detect subsurface defects. While AMT offers significant advantages including material-specific heating optimization and lower power requirements compared to conventional thermographic methods, the technique faces a persistent challenge related to the thermal …

Amplitude Mode At The Superfluid-Insulator Transition On A Random Lattice, Pulloor Kuttanikkad Vishnu, Rajesh Narayanan, Thomas Vojta

Physics Faculty Research & Creative Works

We study the superfluid-insulator quantum phase transition of interacting bosons by means of large-scale Monte Carlo simulations in the presence of both topological and generic quenched disorders. Recent work has demonstrated that the amplitude mode at this transition broadens and localizes in the presence of dilution disorder, whereas it remains a well-defined delocalized excitation for topological (connectivity) disorder. Here, we analyze the crossover between systems with purely topological disorder and systems with additional bond randomness to disentangle the roles that disorder and interactions play for amplitude mode localization. Specifically, we analyze the scalar susceptibility and its spectral density on both …

The Organization Of Serotonergic Fibers In The Pacific Angelshark Brain: Neuroanatomical And Supercomputing Analyses, Skirmantas Janušonis, Ralf Metzler, Thomas Vojta

Physics Faculty Research & Creative Works

Serotonergic axons (fibers) are a universal feature of all vertebrate brains. They form meshworks, typically quantified with regional density measurements, and appear to support neuroplasticity. The self-organization of this system remains poorly understood, partly because of the strong stochasticity of individual fiber trajectories. In an extension to our previous analyses of the mouse brain, serotonergic fibers were investigated in the brain of the Pacific angel shark (Squatina californica), a representative of a unique (ray-like) lineage of the squalomorph sharks. First, the fundamental cytoarchitecture of the angel shark brain was examined, including the expression of ionized calcium-binding adapter molecule 1 (Iba1, …

The Kinetics Of Shj Degradation: Time And Stressor Dependent Chemical Analysis And Simulation, Nicholas Moser-Mancewicz, Jorge Ochoa, Michael Martinez-Szewczyk, Thomas Bantle, Dana Kern, Dirk Jordan, Steve Johnston, Julia E. Medvedeva, Mariana Bertoni

Physics Faculty Research & Creative Works

Despite record efficiencies, the wide adoption of silicon heterojunction is hampered by higher costs and uncertainties in long-term performance. Although recent publications report performance loss rates comparable to other field-deployed cSi technologies, the limited availability of field data and the dispersion in performance degradation results - particularly in open-circuit voltage - remain significant concerns. Various factors, including bulk and interfacial defects, charge carrier recombination dynamics, and environmental stressors such as temperature and humidity, contribute to this degradation. Understanding the mechanisms behind the open circuit voltage degradation as well as the kinetics involved is essential for developing mitigation strategies that enhance …

Thermo-Rheological And Tribological Properties Of Low- And High-Oleic Vegetable Oils As Sustainable Bio-Based Lubricants, Abiodun Saka, Tobechukwu K. Abor, Anthony C. Okafor, Monday U. Okoronkwo

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Vegetable oil-based lubricants have attracted increased research attention in recent decades as sustainable alternatives to conventional petroleum-based lubricants in metal machining. However, more studies are required to fully elucidate the thermo-rheological and tribological properties. This study presents an investigation of the thermo-rheological and tribological properties of different vegetable oils, including low- and high-oleic soybean oil, high-oleic sunflower, safflower, and canola oils. The lubricity, and evolution of viscosity and thermodynamic properties as a function of temperature were investigated to obtain important parameters including the viscosity index, flow behavior index, flow activation energy, specific heat capacity, thermal conductivity, coefficient of friction, contact …

Arc-Jet And Free-Flight Evaluation Of Laminar And Turbulent Diffusion Models On Ablation, Kyle Worden, Andrew Heider, Serhat Hosder

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper investigates the effect of diffusion models on carbon ablation with a parametric study on a slug-calorimeter geometry in arc-jet flow at two enthalpy conditions using two arc-jet flow modeling approaches, and at corresponding enthalpy-matched free-flight conditions using RANS CFD simulations. Additionally, a sphere-cone geometry is modeled at the arc-jet enthalpy matched free-flight conditions and at a high Reynolds number free-flight condition. The approximate-corrected form of Fick's law and the Stefan-Maxwell diffusion models are investigated for equilibrium and finite-rate carbon ablation in laminar and turbulent flows, which is simulated with the Menter-SST turbulence model. The turbulent cases include the …