Digital Commons Network^™

Development Of Catalytic Membranes And Composites For Energy Storage Devices And Nonenzymatic Biosensors, Harish Singh

Doctoral Dissertations

The excessive use of fossil fuels has led to their rapid depletion, causing an energy crisis and environmental issues. Consequently, there's a growing focus on sustainable energy conversion. Electrocatalysts are pivotal in this development, particularly for fuel cells and solar fuel generators, necessitating high-efficiency, cost-effective catalysts for large-scale adoption. Transition metal chalcogenides have emerged as promising electrocatalysts due to their high efficiency, electrochemical tunability, and abundant active sites. This work is divided in two parts. In Part A, we have investigated transition metal chalcogenide and few atom clusters FACs as electrocatalysts for oxygen evolution and reduction, highlighting their structure-property relationships …

Applying Human System Integration Principles To The Investigation, Design And Validation Of Interventions For Self-Escape In Underground Mines, Eugene Adubofour Gyawu

Doctoral Dissertations

This dissertation investigates the use of human systems integration (HSI) to develop technologies for miners’ self-escape during a mine emergency, addressing barriers that compromise miner safety during emergencies.

Recognizing the inherently hazardous nature of underground mining, this study has three core objectives: (1) assessing miners' perceptions of proposed self-escape interventions, (2) designing interventions based on these insights, and (3) validating their effectiveness using experimental testing. This work evaluates self-escape interventions for both coal and metal/non-metal miners using scenario-based surveys, information design reviews, label designs and experimental testing methods varying across three distinct studies.

Results reveal that miners identified improvements to …

Deep Learning And Adaptive Clustering Approaches For Flood Prediction And Efficient Sensor Placement In Missouri, Fahimeh Sharafkhani

Doctoral Dissertations

Floods represent formidable natural calamities, posing a significant threat to communities and infrastructure due to their unpredictable and often devastating consequences. The occurrence of floods is influenced by a convergence of meteorological, hydrological, and geographical factors, resulting in changes to the patterns of rising water levels. Machine learning models have emerged as favored tools in recent times for modeling water levels and enhancing the precision of flood predictions. This research employs both supervised and unsupervised machine learning models, with the main objective of improving the accuracy of flood predictions and sensor placement. Four distinct deep learning models are used to …

Measurement Method And Applications Of Transfer Function In Rf Desensitization Problem, Xiangrui Su

Doctoral Dissertations

Radio frequency (RF) desensitization issues comprise two components: noise radiation sources and the transfer function from noise sources to the victim antenna. RFI is a critical challenge in modern electronic systems, particularly in densely packed environments. This work presents a comprehensive study of RFI, addressing key aspects through three novel contributions. First, a transfer function measurement method is developed for compact metallic enclosures. This method provides a precise characterization of the electromagnetic (EM) environment within confined spaces, enabling accurate identification of interference pathways. Second, an EM emission management analysis framework is proposed, leveraging transfer functions to quantify and mitigate interference …

Topics On Ai Fairness Preferences In Kidney Transplantation, Mukund Telukunta

Doctoral Dissertations

Modern kidney transplantation incorporates artificial intelligence (AI) decision-support systems which exhibit social discrimination due to biases inherited from training data. Although researchers have proposed various group-based fairness notions to assess biases in AI, it remains uncertain which criterion is most suitable for evaluating biases in such complex healthcare systems. This dissertation explores human perception of fairness to identify the most appropriate fairness criterion for assessing AI tools in kidney transplantation, focusing on the preferences of non-expert (e.g. public, patients) stakeholders. The study examines two distinct AI systems employed in kidney transplantation: a classification model and a regression model. Human subject …

The Real-Time Detection Infrastructure Of Ligo, Virgo, And Kagra: Data Products, Current Performance, And Future Developments, Sushant Sharma Chaudhary

Doctoral Dissertations

The discovery of the binary neutron star merger event GW170817 marked the dawn of Multi-Messenger Astronomy (MMA) with Gravitational Waves (GWs). Such multi-messenger events are of immense scientific interest due to the wealth of information they provide through joint observations across different messengers. In this rapidly evolving field, prompt identification and timely distribution of alerts is critical for follow-up observations.

This work offers a comprehensive overview of the LIGO-Virgo-KAGRA (LVK) Collaboration’s low-latency analysis pipeline for GW events, covering key stages from calibration and data analysis to the issuance of public alerts. I examine the latency and accuracy of each stage …

Systematic Esd Analysis And Modeling For Electronic Device, Zhekun Peng

Doctoral Dissertations

Systematic ESD analysis provides good pre-compliance to ESD robustness evaluation on the electronic device from device level to component/system level to on-chip level. The whole process involves corona discharge on display, system level ESD analysis on PCB for race condition and transient response and 3D IC package impact to on-die ESD.

ESD to the display cover glass can damage touchscreen traces by sparkless corona discharges on the glass surface. A non-linear time dependent transmission-line model is proposed to model corona streamer propagation in terms of the coupling current and propagation speed. Results are highly promising to model the corona discharge …

Assessing And Comparing Geophysical Methods For Resolving Shallow Subsurface Geology, Abdullah Basaloom

Doctoral Dissertations

Geophysical methods are essential tools for investigating shallow subsurface structures, offering non-invasive means to characterize geological features and detect anomalies. Techniques such as electrical resistivity tomography (ERT), towed Transient Electromagnetic (tTEM), seismic refraction, magnetic, gravity, and magnetotelluric (MT) are commonly employed to image subsurface conditions with high resolution.

This study started with an in-depth analysis of comparing results co-located in space to assess uncertainties and resolution in the obtained resistivity models in the Kansas River Alluvial Aquifer (KRAA). Our results provided a quantitative interpretation of resistivity estimates between different geo-electrical methods (ERT, tTEM and DPEC). Following this, we provided a …

The Structure, Properties And Dissolution Behaviors Of Phosphate Glasses, Han Zhang

Doctoral Dissertations

The poor chemical durability remains a critical challenge for the application of phosphate glasses. This study investigates the compositional influences on the structure, properties and chemical durability of Li2O-ZnO-P₂O₅ glasses. Their structural characteristics were analyzed utilizing high-performance liquid chromatography, Raman spectroscopy, and X-ray photoelectron spectroscopy. The incorporation of (Li2O+ZnO) in LZeq glasses depolymerizes the phosphate network. In LZ40P and LZ45P glasses, Li⁺ initially replaces Zn²⁺ associated with non-bridging oxygens (NBOs) in Q² tetrahedra. Once the substitution in Q² is complete, further Li⁺ incorporation leads to the replacement of Zn²⁺ in Q^{1 …}

Optical Detection Of Instantaneous Microwave Frequency And Displacement, Behzad Boroomandisorkhabi

Doctoral Dissertations

Research presented in this research is focused on developing and implementing novel photonic systems for instantaneous microwave frequency and displacement measurement, emphasizing cost-effectiveness, scalability, and high resolution. The research is encapsulated in three core studies: the design of all-fiber ultrafast ranging Lidar for medical motion management, the application of dispersive interferometry using picosecond laser pulses for laser ranging, and the integration of microwave photonic systems with digital signal processing (DSP) for enhanced measurement precision.

The work achieves micrometer-scale displacement accuracy and microwave frequency resolutions within ±1 MHz across wide dynamic ranges by leveraging dispersive interferometry and time-stretch techniques. The studies …

Design Of Real-Time And Energy-Efficient Driver Assist Systems Using Electroencephalogram And Neuromorphic Computing, Nathan Alan Lutes

Doctoral Dissertations

Despite the technological breakthroughs in advanced driver assist systems, distracted driving persists as a major challenge to roadway safety. This investigation advances the body of knowledge towards a solution by developing an individualized driver-state detection method using electroencephalogram (EEG) and neuromorphic computing to provide a less invasive and more energy efficient ADAS solution. It furthermore explores the changes in brain functional connectivity under distracted conditions to better understand brain state information that could be used for neuro-feedback intervention systems. The first contribution introduces the concept of using Convolutional Spiking Neural Networks (CSNNs) for recognition of patterns with movement-intention predictive power …

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 …

Dynamic Response, Assessment, And Retrofitting Of Prestressed Concrete Bridge Girders Subjected To Lateral Impact Loads, Haitham A. Abdelmalek

Doctoral Dissertations

Over height vehicle collisions pose a growing threat to the resilience of bridge infrastructure across the United States. According to the American Road & Transportation Builders Association (ARTBA, 2024), approximately 36% of all U.S. bridges require major repair or replacement, with an estimated cost of $400 billion. This dissertation investigates the structural dynamic response, damage assessment, and retrofitting strategies for prestressed concrete (PC) bridge girders subjected to lateral impact loading.

The research comprised two main phases: (1) numerical modeling and (2) experimental testing. A validated 3D nonlinear finite element (FE) model was developed to conduct parametric studies on impact behavior, …

Nutrient Fate, Mass Balance, Species Selection, And Plant Management Strategies With Floating Treatment Wetlands, Carla Campbell

Doctoral Dissertations

Excess nutrients in shallow urban ponds can lead to harmful algal blooms, low dissolved oxygen, and internal phosphorus cycling. These effects can compromise municipal water supplies and cause negative impacts on fisheries and recreation. Floating treatment wetlands (FTWs) show promise to mitigate surface water nutrient pollution. However, despite recent research, many aspects of FTWs remain poorly characterized. The contribution of FTW components to nutrient removal, local species selection, and plant management strategies were the focus of this dissertation. Mesocosm experiments revealed that the combination of plants and coir fiber growth media in FTWs appeared to positively affect plant biomass gain …

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 …

Synthesis Of Graphene Using Carbonaceous Materials In An Ultrasonic Reactor, Paul Chukwuma Ani

Doctoral Dissertations

The synthesis of high-quality graphene from sustainable carbonaceous feedstocks offers an avenue to reduce the environmental and economic costs associated with conventional graphite-based production. This research investigates the co-utilization of biochar and graphite as precursors for graphene fabrication in an ultrasonic reactor. Biochar was produced from biomass via downdraft gasification at 850 °C, yielding a high fixed-carbon, partially graphitized material with favorable surface area and porosity. Graphite, selected for its crystalline structure, was investigated with biochar to assess the influence of precursor composition on exfoliation efficiency, layer thickness distribution, and defect density. Ultrasonic-assisted liquid-phase exfoliation was employed, with process parameters …

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 …

Characterization And Deportment Of Anode Impurities In Copper Electrorefining, Charles Michael Campbell

Doctoral Dissertations

The objective of this research was to study the deportment of the group 15 elements, arsenic, antimony and bismuth during copper electrorefining. Samples were collected from six industrial copper anodes with different compositions. Specimens were physically characterized and electro refined to understand the differences in the behavior of selected impurities. Inclusions in the cast metal structures were characterized using automated scanning electron microscopy and energy dispersive spectroscopy to measure and correlate their size, shape and composition. Arsenic and lead were found to have a positive correlation between concentration and size of inclusions. Using wavelength dispersive spectroscopy, multiphase inclusions were examined, …

Data-Driven Mulitiscale Modeling Of Electrochemical Transport, Non-Linear Electrical Contact, And Additive Manufacturing Processes, Emmanuel Olugbade

Doctoral Dissertations

The growing demand for high-efficiency energy systems and advanced manufacturing technologies requires predictive frameworks that link atomic-scale physics with engineering-scale performance. This dissertation develops a unified multiscale modeling approach that integrates molecular dynamics, density functional theory, finite-element analysis, and machine learning to connect structure, transport, and performance across materials and processes. Depending on the interactions involved, the framework employs loose coupling for parameter transfer, tight coupling for two-way feedback, and hybrid coupling where machine-learning surrogates accelerate high-fidelity simulations while retaining physical interpretability. In electrochemical systems, an XGBoost-enhanced single-particle model reproduces P2D-level electrolyte potential dynamics at roughly one-hundredth the computational cost, …

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 …

Advancements In Signal Processing And Image Reconstruction For Active Microwave Thermographic Measurements, Logan Martin Wilcox

Doctoral Dissertations

Active microwave thermography, or AMT, is a coupled electromagnetic-thermographic nondestructive testing and evaluation technique. AMT has found success in a variety of inspection needs in the aerospace, space, and infrastructure fields due to its unique type of thermal excitation. During an AMT inspection, a specimen is exposed to microwave energy from a radiating source (i.e., an antenna). This exposure to microwave energy results in dielectric/magnetic heating, which causes an increase in temperature and potential defect indications to manifest on an inspection surface (which is measured via an infrared camera). Due to the use of an antenna, there is a spatially …

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 …

Identification Of Corrosion Damage, Vibration, And Loose Conections In Aircraft Data Transmission Lines Using Reflected And Transmitted Signals; Formulation Of Vegetable Oil-Based Nanofluids As Cutting Fluids For Mql Machining, Saidanvardzhon Valiev

Doctoral Dissertations

This research presents a novel Frequency Domain Transmitometry (FDT) method that uses transmitted signals (S21) to detect and characterize aircraft data transmission lines (ADTL) corrosion damage without additional reflectometry circuitry. Corrosion experiments were conducted according to ASTM G85-A5 over 14 weeks. Combined FDT and reflected signals (S11) analyses revealed distinct three-peak signatures associated with damage and corrosion. The square root of the Area Under the Curve (AUC) of the FDT damage peak and the Full Width at Three-Quarter Maximum (FW3QM) of the S11 damage peak is correlated with corrosion propagation depth and width. S11 signals were further used for vibration …

Process-Structure-Property Relationships In Laser Powder Bed Fusion Produced 17-4 Ph Steel, Ben Brown

Doctoral Dissertations

Laser powder bed fusion (LPBF) is a metal additive manufacturing method that produces non-traditional microstructures as a result of the rapid solidification and thermal cycling inherent to the process. When using LPBF-produced material in application, these unique microstructures challenge the applicability of well-developed mechanical property databases achieved by conventional heat treatments. For wider adoption of this technology, a more holistic understanding is necessary on how process attributes develop material structure, which dictate mechanical properties. This dissertation explores the process structure-property relationships in LPBF 17-4 PH steel through systematic evaluation of atmospheric processing and heat treatment effects on microstructure and mechanical …