Digital Commons Network^™

Applications Of Tetramethyl-Guanidine Supported Cationic Transition Metal Sites Towards C─N Bond Construction Methodologies And [3+2] Cycloaddition Reactions, Suraj Kumar Sahoo

Doctoral Dissertations

"We present a family of divalent cationic bipodal and tripodal M(II) reagents (M = Mn, Fe, Co) supported by superbasic tetramethyl-guanidinyl (TMG) residue framework with applications towards C─N bond construction methodologies. These cationic reagents possess unique characteristics since their enhanced Lewis acidity facilitates in situ elaboration of the primary nitrene-transfer product (aziridine). Indeed, further aziridine-ring opening and cycloaddition of several dipolarophiles (nitriles, alkenes, ketones) permits the three-component synthesis of valuable five-membered N-heterocycles, commonly found in pharmaceuticals and agrochemicals.

We undertake a more systematic study to unravel parameters that make certain divalent metal sites more suitable as catalysts for the in-situ …

Development Of Ligands And Metal Complexes With Weakly Coordinating Apical Elements And Their Application To Nitrene Insertion And Addition To C‒H And C=C Bonds, Meenakshi Sharma

Doctoral Dissertations

"We present a family of triangular coinage metal M₃Cl₃ complexes [M = Cu (I), Ag (I)] supported by antimony [Sb (III)], and bismuth [Bi (III)]-centered highly basic tetramethyl-guanidinyl [TMG₃trphen-E] (E = Sb, Bi) ligand frameworks with their applications as catalysts toward the construction of C‒N bond through aziridination and amination reaction methodologies.

The [(TMG₃trphen-Sb)Cu₃(µ-Cl)₃] catalyst gives better yields of aziridines with styrenes than [(TMG3trphen-Bi)Cu₃(µ-Cl)₃] with PhINTs as a nitrene source. However, the catalytic reactivity of both catalysts is enhanced by an electrophilic nitrene, PhINTces for …

Sensor Embedding And Thermal Monitoring Strategies For Laser-Foil-Printing Additive Manufacturing, Tunay Turk

Doctoral Dissertations

"This work investigates Laser Foil Printing (LFP), a novel metal additive manufacturing (AM) process that fabricates parts layer-by-layer using metal foils. To enhance LFP productivity, the process steps were optimized, and an 88.1% reduction in processing duration was achieved. A unique aspect of this study was the introduction of laser polishing as an edge polishing technique within the LFP process. This innovative approach, employing an overlapping spiral pattern, leverages selective laser remelting and erosion to effectively suppress elevated edges. To stabilize the molten melt pool, a discrete spot scanning strategy was implemented. The fabricated parts were subjected to detailed analysis, …

Raft-Based Polymer And Nanoparticle Materials For Traumatic Brain Injury Treatment And Diagnostics, Aaron Priester

Doctoral Dissertations

"Traumatic brain injury (TBI) is a leading cause of death and disability worldwide. Neurodegenerative diseases that develop post-TBI can be, in part, attributed to DNA and cell-damaging reactive oxygen species (ROS) and lipid peroxidation products (LPOx). This thesis focused on overcoming the limits of current TBI material treatment approaches by employing a RAFT (reversible-addition fragmentation chain transfer) polymer approach that incorporated novel therapeutic, diagnostic and peptide-targeting monomers. An improved nanoparticle synthesis approach was also developed. Thiol and thioether-containing monomers neutralize both ROS and LPOx while Gd-containing monomers with enhanced magnetic resonance imaging (MRI) contrast provide diagnostics and material tracking in …

Vibration Modeling Of Rectangular Plates And Application To Solar Cell Dust Mitigation, Jeremiah John Rittenhouse

Doctoral Dissertations

"Many engineering structures can be modeled as rectangular plates, including solar cells. Carefully controlled plate vibration can be useful to solve an engineering problem, such as lunar dust accumulation on solar cells, which blocks light and reduces power generation. For this application, plate vibration at resonance is studied and used experimentally to eject lunar dust from a solar cell.

Piezoelectric actuator placement on the inactive side of a solar cell to induce vibration dust mitigation from the active side of the cell is presented in this work. Three solar cell prototypes were created and tested for efficacy, resulting in an …

Atmospheric Transport Of Radionuclides, Meteorological Data Mining & Synthesis For Site Data Supplementation, Ben Yao Sonpon

Doctoral Dissertations

"This research aligns with the NRC's vision of implementing risk-informed decision-making to support its regulatory charter. The suite of tools developed includes automated procedures for data mining and extracting meteorological (met) data from various national and regional repositories. A second data analytics tool automates the process of data fusion into a uniform format while preserving data fidelity. Autocorrelations were then established, and correlation coefficients were calculated between the Callaway Nuclear Power Plant (Callaway) and nearby off-site weather stations. The complexity of these correlations depends on factors such as physical proximity, geographic features, and topology, potentially necessitating multivariate analysis (MVA). Furthermore, …

Shock Wave And Vortex Ring Dynamics From Explosively Driven Shock Tunnels, Rachel Louise Bauer

Doctoral Dissertations

"Blast and shock tubes are frequently used to create shock waves to study their effects and impacts on structures, humans, and personal protective equipment. These tubes are also found in other industries including wind tunnels for aerodynamic testing, jet engines for propulsion research, spacecraft reentry simulations, and industrial applications such as material testing and high-velocity impact studies. Despite their widespread use, there is no standard design, with variations in geometry, size, and energy sources. Current research only evaluates the peak pressure of the shock wave produced and does not consider the effects of changing the size or geometry of the …

Transport And Plugging Behavior Of Co2-Resistant Preformed Particle Gels In High Conductive Channels For Conformance Control, Adel Alotibi

Doctoral Dissertations

"Improving oil recovery is essential with rising global oil demand and declining production in mature fields. CO₂ flooding has been widely applied as a major Enhanced Oil Recovery (EOR) method due to its effectiveness in boosting oil recovery while enabling safe carbon storage in the subsurface. However, in fractured and highly heterogeneous reservoirs, CO₂ often flows through paths of least resistance, leading to early breakthrough or quick excessive CO₂ production and leaving substantial oil in unswept zones or areas. Traditional in-situ polymer gels have been applied to control CO₂ flooding conformance, their performance has been varied, …

Selected Topics In Blockchain-Aided Iot Inference, Yiming Jiang

Doctoral Dissertations

"Blockchain has recently been considered in the Internet of Things (IoT) to secure data exchanges and storage across various engineering applications. This newly emerging blockchain-aided IoT (BIoT) network has been applied to a great deal of security-related applications. However, the BIoT still has the vulnerability that can be exploited by attackers, potentially impairing the performance of BIoT applications. Despite this, research addressing the vulnerability has been limited. This work presents four studies aimed at addressing critical gaps in current BIoT research.

The first study introduces a Time-Restricted Double-Spending Attack (TR-DSA) model for Proof-of-Work (PoW)-based blockchains, where the adversary only conducts …

Application Of Artificial Intelligence Techniques To Improve Leadership Decision Making With Uncertainty, Michael David Parrish

Doctoral Dissertations

"Every good leader is a good manager, but not every good manager is a good leader. The difference between the leader and the manager is critical decision-making. Today’s decision-making environment is characterized as Volatile, Uncertain, Complex, and Ambiguous (VUCA). With the exponential increase in the technical capabilities of systems, the human has become the weakest link in the use of such systems. To remain relevant, good leaders must continuously adapt to new advances in technology and processes.

The research contributions of this work provide several unique and novel solutions for leaders to utilize artificial intelligence tools to improve and optimize …

Experimental Investgation Of Core Fluid And Heat Transfer Of Pwr By Using Advanced Measurments Techniques, Saud Aldawood

Doctoral Dissertations

This comprehensive study investigates the thermal-hydraulic mechanisms and convective heat transfer characteristics within (PWRs), with a focus on (SMRs) under both single-phase and two-phase bubbly flow conditions. Specifically, the research investigates the complex bubble dynamics in two-phase flow rod bundles, which are crucial for understanding reactor behavior during loss-of-coolant accidents (LOCA). Employing an advanced experimental setup developed at the (mFReel) at MST, this work measures critical parameters such as void fraction, bubble passage frequency, bubble velocity, bubble chord length, and interfacial area concentration (IAC) using a four-tip optical probe across various locations in the rod bundle. The findings reveal that …

On The Importance Of Novel Adsorption Processes And Structured Adsorbents For Biogas Upgrading And Storage, Kyle Newport

Doctoral Dissertations

The current adsorption processes investigated for biogas upgrading encounter severe challenges with regards to both adsorbents and processes, which necessitate the design and development of novel approaches to effectively separate carbon dioxide from methane and, hence, produce pipeline-grade renewable natural gas (RNG) as a fuel. These key challenges include (i) moderate CO2/CH4 selectivity, (ii) relatively long cycle times, (iii) high regeneration energy requirements, (iv) high-pressure drop, and (v) short adsorbent lifetime. The current biogas upgrading processes typically rely on pressure swing adsorption (PSA) or temperature swing adsorption (TSA). While PSA cycles are fast, the system requires large amounts of energy …

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 …

Deep Learning Architecture Design For Nano-Satellite Image Super-Resolution, William Everette Symolon

Doctoral Dissertations

Increasing threats to U.S. national security satellite constellations have resulted in an increased interest in constellation resilience and satellite redundancy. NanoSats have contributed to commercial, scientific and government applications in remote sensing, communications, navigation, and research. They also have the potential to enhance satellite constellation resilience. However, the inherent size, weight, and power limitations of NanoSats enforce constraints on imaging hardware; the small lenses and short focal lengths result in imagery with low spatial resolution, which limits the utility of CubeSat images for military planning purposes and national intelligence applications. This research proposed a deep learning architecture capable of enhancing …

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 …

Navigation In Underground Mine Environments: A Simulation Framework For Quadruped Robots, Yixiang Gao, Kwame Awuah-Offei

Mining Engineering Faculty Research & Creative Works

Quadruped robots have shown significant potential for navigating complex and hazardous environments, such as underground mines, where traditional wheeled or tracked systems have limitations. However, their development and deployment are hindered by the disparity between controlled laboratory testing and real-world conditions and the lack of tools (e.g., simulation testbeds) that expedite the required development and testing. This work develops a simulation testbed for expediting and advancing navigation algorithms, perception systems, and control strategies for quadruped robots in subterranean and hazardous environments. By utilizing high-fidelity 3D maps, ranging from intricate cave systems to real-world sites like the Edgar Mine, simulation environment …

Cracking The Code: Harnessing Serpentinization-Driven Micro-Crack Networks For Hydrogen Generation And Subsurface Resource Recovery, U. Mutlu, G. Boitnott, A. Lisjak, J. Ha, O. Mahabadi, P. Connolly, B. N. Tunnell, T. Sherizadeh, S. Nowak, J. E. Olson

Mining Engineering Faculty Research & Creative Works

This study focuses on simulating volume-increasing processes caused by natural hydrogen-generating serpentinization, a reaction in which olivine and pyroxene typically transform into serpentine minerals. The volume increase leads to crack propagation along grain interfaces and new crack generation within unreacted crystals (aka grains). The interplay between thermo-hydro-mechanicalchemical (THMC) conditions plays a critical role in the initiation, propagation, and coalescence of various fracture surfaces, which enhances permeability and can accelerate serpentinization and hydrogen production rates. In the scenarios considered, chemical reactions between formation brine and reactive minerals result in volumetric expansion, generating stress and promoting the propagation of micro-cracks. Our results …

Mapping Biomedical Ontology Terms To Ids: Effect Of Domain Prevalence On Prediction Accuracy, Thanh Son Do, Daniel B. Hier, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

This study evaluates the ability of large language models (LLMs) to map biomedical ontology terms to their corresponding ontology IDs across the Human Phenotype Ontology (HPO), Gene Ontology (GO), and UniProtKB terminologies. Using counts of ontology IDs in the PubMed Central (PMC) dataset as a surrogate for their prevalence in the biomedical literature, we examined the relationship between ontology ID prevalence and mapping accuracy. Results indicate that ontology ID prevalence strongly predicts accurate mapping of HPO terms to HPO IDs, GO terms to GO IDs, and protein names to UniProtKB accession numbers. Higher prevalence of ontology IDs in the biomedical …

Online Learning-Driven Human Intent Estimation And Control For Human-Robot Interaction, Irfan Ganie, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a novel Stackelberg-game theoretic multilayer-online learning framework for cooperative control of nonlinear Physical Human-Robot Interaction (pHRI), where the human is modeled as the leader guiding a robot follower. This hierarchical interaction is captured as a dynamic Stackelberg game, with the human's intention estimated in real-time through online multilayer neural networks (MNNs). We introduce SVD-based weight update laws for actor-critic MNNs, which approximate value functions and control inputs for both human and robot, eliminating the need for predefined basis functions. In this framework, the human objective is first inferred and used to guide the robot actions by shaping …

An Entropy-Bounded, General, Model-Based Framework For Lossy Compression Of Sensor Data, Steven Thompson, Maciej Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

In many industries, digital twinning has become an indispensable element of advanced technologies. However, digital twins are heavily reliant on extensive Internet of Things (IoT) sensor measurement data to function effectively. Consequently, data mining has become a lucrative endeavor, akin to gold rushes in the XIX century. However, the substantial volume of collected data often stresses the storage capacities for smaller to medium-sized enterprises, necessitating efficient compression techniques. Error-bound lossy compression offers substantial data reduction advantages, but introduces distortion that, when uncontrolled, can adversely affect analysis. This paper proposes an information optimization scheme that employs information entropy as a comprehensive …

Multi-Model Safe Neuro-Optimal Output Tracking Control Of Autonomous Surface Vessels With Explainable Ai, Behzad Farzanegan, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a safety-aware deep reinforcement learning (DRL)-based trajectory tracking control of autonomous surface vessels (ASVs). A multilayer neural network (MNN) observer estimates the ASV's state and uncertain dynamics. By utilizing the estimate state vector from the observer, a safety-aware DRL-based optimal policy is formulated using control barrier function (CBF) and Karush-Kuhn-Tucker (KKT) conditions. An actor-critic MNN with singular value decomposition (SVD)-based update mitigates vanishing gradients. To enhance adaptability, an online safe lifelong learning (SLL) scheme counters catastrophic forgetting across varying ASV dynamics. The Shapley Additive Explanations (SHAP) method identifies key features influencing the control policy. Simulations on an …

Online Adaptive Optimal Tracking Control Of Uncertain Strict Feedback Discrete-Time Systems With Hardware Verification Using A Quadrotor Uav, Maxwell Geiger, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article considers the infinite time horizon optimal tracking control problem for discrete time (DT) partially uncertain strict feedback systems with application to quadrotor UAVs. First, the strict feedback DT system is transformed into an equivalent affine nonlinear DT system in terms of tracking error dynamics. The optimal tracking control problem is solved using an augmented system approach, where a horizon of future reference trajectory points are used in the augmented state, as compared to using a single point. The internal dynamics of the original nonlinear strict feedback system and the transformed affine system in terms of error dynamics are …

Enhancing Measurement Accuracy In Industrial Applications: The Impact Of Sensor Data Imputation On Model Parameter Estimation, Steven Thompson, Michkath Omanda Bouraima, Maciej Jan Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

Digital twins are meant to revolutionize the manufacturing industry by enabling advanced condition monitoring and predictive maintenance processes. However, disruptions within the manufacturing process, such as sensor malfunctions or connectivity issues are inevitable and will cripple these advanced analysis methods if not properly addressed. Therefore, efficient data management and analysis practices are key to advancing this technology. This work examines the impact of missing data imputation on model parameter estimation, a crucial task in developing models for digital twins. We theoretically derive the Cramer-Rao Lower Bound (CRLB) for a DC signal with an unknown scalar parameter in the presence of …

Active Microwave-Thermographic Signal Reconstruction, Logan M. Wilcox, Emma T. Bohannon, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is a coupled electromagnetic (EM) and thermographic nondestructive testing and evaluation (NDT&E) technique. AMT utilizes a radiating EM source (e.g., an antenna) that induces dielectric/magnetic heating on a specimen under test (SUT) which is subsequently spatiotemporally imaged with an infrared (IR) camera. As all antennas have spatial variation in their radiated power density, a nonuniform thermal excitation results within (or on the surface of) the SUT. This nonuniform heating causes uncertainty in defect detection and has the potential to lead to false positives and/or negatives. To this end, thermographic signal reconstruction (TSR), a well-established thermographic signal …

Reinforcement Learning-Based Nonlinear Optimal Discrete-Time Control Of Power Systems, Vijay Kumar Singh, Behzad Farzanegan, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a partially model-free adaptive optimal tracking control method for power systems, specifically targeting a synchronous generator connected through a reactive transmission line. By integrating the tracking error dynamics with reference trajectory dynamics, an augmented system is created. A discounted performance function is introduced to address the nonlinear tracking problem optimally. Unlike traditional methods that compute feedforward and feedback terms separately, the proposed approach calculates both simultaneously by minimizing the discounted performance function. The discrete-time tracking Bellman and Hamilton-Jacobi-Bellman (HJB) equations are derived, and a reinforcement learning (RL)-based technique is employed to solve the optimal policy online without …

Enhancing Fiber Optic Interferometric Sensing With Microwave Photonics-Based Dispersion Fourier Transform And Integrated Magnitude–Phase Analysis, Chen Zhu, Ruimin Jie, Chenxi Huang, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Fiber optic inline interferometers are widely used for high-precision sensing due to their sensitivity, compactness, and immunity to electromagnetic interference. Traditional optical spectral analysis methods suffer from limited dynamic range due to free spectral range (FSR) constraints, while microwave photonic filtering (MPF) techniques based on dispersion Fourier transform (DFT) provide an alternative by mapping optical signals into the radio frequency (RF) domain. However, conventional passband frequency tracking in MPF systems has limited sensitivity, and the recently demonstrated phase-based methods, though highly sensitive, are constrained by phase wrapping beyond 2π. In this work, we propose and experimentally demonstrate an integrated magnitude–phase …

Distributed Sapphire Fiber Bragg Grating-Based Thermal Profiling Of Submerged Entry Nozzles, Farhan Mumtaz, Hanok W. Tekle, Bohong Zhang, Xiaodong Li, Sunday Abraham, Bryant Mathis, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This article focuses on the application of sapphire fiber Bragg gratings (FBGs) for instrumentation in submerged entry nozzles (SENs) within the steelmaking industry. The SEN is pivotal for transferring molten steel from a tundish to a mold, while preventing the infiltration of oxygen and nitrogen from the surrounding environment. Maintaining optimal flow conditions in the mold is crucial for ensuring casting process stability and maintaining high-quality steel. Sapphire FBG sensors have been instrumented in SENs to enable distributed thermal mapping for monitoring the health of the SEN. The optical sensor comprises three cascaded sapphire FBGs inscribed using femtosecond (FS) laser …

Filter Based Motor Control For Robotic Applications, Shuzan Kumar Sarkar, Noah Wilding, Shruti Pandey, Nicholas Hawkins, Michael L. Mcintyre

Electrical and Computer Engineering Faculty Research & Creative Works

Controlling coreless DC motor in the field of humanoid robotic application involves considering various surrounding electromagnetic environment interference and sudden change of load with parameters variation of motor dynamics which makes the system complex. This paper presents a filter-based control scheme for a coreless DC motor drive system using an H-bridge inverter as the input circuit of the motor which is easy to implement and cost effective. From the electromagnetic characteristics, the dynamic model of the motor along with the control scheme is implemented in the commercial software PLECS. Then the effectiveness of this approach is validated through simulations demonstrating …

Ibis Model Simulation Accuracy Improvement With Slew Rate Correction, Yifan Ding, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

The accuracy of Power-Supply-Induced Jitter (PSIJ) simulation in Input/Output Buffer Information Specification (IBIS) models is critical for ensuring robust high-speed signal integrity analysis, but it lacks accuracy in predicting the PSIJ when the pre-driver exists in the model. Previous studies have proposed methods to improve IBIS PSIJ simulation accuracy with pre-driver effect included in the IBIS switching coefficients modification process. However, these methods fail to accurately model the output waveform slew rate change with varied power noise. In this work, an improved modification method was proposed to incorporate power-aware characteristics into the modified IBIS model, thereby improving the accuracy of …