Engineering Commons^™

Performance Limiting Factors For Silicon Anodes In Lithium-Ion Batteries, Najmaddin Bashirzada

Theses and Dissertations

The rising global demand for high-performance and sustainable energy storage solutions has placed lithium-ion batteries (LIBs) at the forefront of technological progress. However, the energy density limits of traditional graphite anodes require the investigation of alternative materials. Silicon (Si), with its high theoretical capacity, is a promising anode material. Still, its practical use faces major challenges such as volumetric expansion, unstable solid electrolyte interphase (SEI) formation, and low conductivity. This thesis examines the electrochemical behavior and limitations of Si-based electrodes using coin cells and ex-situ three-electrode cells. A comparison of electrochemical testing methods – i.e., Galvanostatic Intermittent Titration Technique (GITT) …

Downwind-Upwind Flux Path Analysis Method For Model Reduction Performance Evaluations, Christian Robert Smith

Theses and Dissertations

Large, complex chemical kinetic models have long since been limited by the computational cost it takes to evaluate said model. Over time many reduction methods have been developed to combat this computational cost. However, very little has been done towards evaluating the limitations of reductions as a way of understanding the original model’s characteristics. This paper aimed to use a path flux analysis-based reduction algorithm to rapidly develop multiple reduced mechanisms for a 96 species FFCM-2 methane chemical kinetic model as well as an 858 species n-Dodecane chemical kinetic model. The goal of formulating these reduced mechanisms was to identify …

Towards Accurate First-Principles Modeling In Heterogenous Catalysis: Ethane Dehydrogenation And Hydrogenolysis Over Pt Catalysts, Mubarak Ayo Bello

Theses and Dissertations

First-principles modeling has become central to heterogeneous catalysis research, offering mechanistic insight and guiding catalyst design, yet conventional approaches often struggle to accurately describe complex catalytic systems due to methodological uncertainties, simplified assumptions, and the structural diversity of nanoparticle catalysts. This dissertation addresses these challenges using ethane dehydrogenation (EDH) and hydrogenolysis (EH) over platinum catalysts as model systems. The first study benchmarks density functional theory (DFT) functionals against the random phase approximation (RPA) for the EDH network on Pt(111), identifying cost-effective functionals and demonstrating the efficiency of BEEF-vdW ensembles for capturing functional uncertainty. The second study (addressed in prior work) …

Multiphysics Modeling, Analysis, And Design Of Ceramic Hollow Fiber Membranes For Oxygen Separation, Hamed Abdolahimansoorkhani

Theses and Dissertations

Oxygen plays a central role in numerous industrial processes. Several technologies have been reported for producing oxygen from air. Among them, oxygen transport membrane (OTM) technology—based on mixed-conducting, gas-tight ceramic membranes—has attracted significant attention due to its high oxygen selectivity, relatively low capital and operating costs, and versatility for both ex-situ and in-situ applications. Mathematical modeling of OTMs offers a powerful tool to investigate internal multi-physics transport phenomena, providing deeper insight into fundamental mechanisms while serving as a cost-effective approach for optimizing membrane stack designs.

After a comprehensive introduction, in the first part of this dissertation (chapter 2), a comprehensive …

A Building Block Approach To Certification By Analysis Applied To A Ditching Analysis, Preliminary Studies, Sean Taylor

Theses and Dissertations

Extended Twin-Engine Operations (ETOPS) certification ensures safe trans-oceanic operation of transport category aircraft. A critical aspect of ETOPS certification is compliance with ditching regulations. The importance of ditching analysis has grown significantly and come under greater scrutiny because of the ‘Miracle on the Hudson’ incident. For transport category aircraft certified under 14 CFR 25 regulations, compliance with ditching requirements, rests on two major components. First, demonstrating acceptable aircraft dynamic behavior during the ditching event and second, ensuring the airframe can withstand the loads generated because of water impact.

Historically, original equipment manufacturers (OEMs) relied on comparisons to existing aircraft with …

Implicit Neural Representation For Image Reconstruction, Canyu Zhang

Theses and Dissertations

Image reconstruction seeks to restore corrupted images and recover visual content that has been lost or degraded. Such degradation may result from low resolution, occlusion, masking, or shadow interference. This problem has become an increasingly significant research topic, as visual information plays a central role in almost every aspect of modern life. Neural network based approaches have recently emerged as highly effective solutions for this task. In particular, convolutional neural networks and transformer based architectures have demonstrated remarkable success in producing visually convincing reconstructions. However, these models remain constrained in several important ways, one of the most critical being that …

Recognizing The Unexpected: Deep Learning Across Complex Environments, Ge Song

Theses and Dissertations

Ensuring the security, trustworthiness, and operational integrity of modern autonomous and cyber-physical systems presents a critical challenge. While widely utilized in various engineering applications, such as intelligent transportation and industrial manufacturing, these systems require robust monitoring frameworks to identify unexpected anomalies in real-time, thereby maintaining operational safety and efficiency. This dissertation develops advanced deep learning methodologies for anomaly detection and health monitoring, with a particular emphasis on semisupervised reconstruction-based approaches that identify anomalies in complex environments using models trained only with normal operational patterns.

Building on this theme, the first study focuses on analyzing pedestrian behavior and detecting anomalies at …

Spectral Modeling Of Electromagnetic Radiation From Power Converters, Regan A. Varner

Theses and Dissertations

Switching power converters are increasingly utilized in contemporary electronics. They are becoming more compact and operate at higher frequencies, which contributes to radiated electromagnetic interference (EMI). This EMI is important to quantify for electromagnetic compatibility of the converters with other nearby systems. In this thesis, analytical models have been developed for both ideal and non-ideal switching waveforms, employing piecewise functions to describe time-domain waveforms, with their corresponding frequency spectra derived and compared to empirical spectra. The results demonstrate that the comparisons with measured frequency data exhibit agreement with the analytical models up to approximately 25 MHz. Additionally, our analysis indicates …

Calculating Surface Current Velocities From Video Generated From A Near Forward-Facing Camera, Colby James Weeks

Theses and Dissertations

This work presents a camera system for estimating surface currents. A combined camera and IMU system provide high resolution images and high precision orientation information, respectively. This eliminates the need for leveling and enables forward looking operation. The hardware stack includes a Lucid Vision Triton TRT162S monochrome camera, an SBG Ellipse D with dual antenna GNSS for precise pose, and an Nvidia Jetson Orin for acquisition and processing. The Ellipse D provides a hardware trigger at 10 Hz to time stamp each frame and to synchronize images with inertial measurements.

A camera calibration step estimates the intrinsic camera parameters and …

Towards Robust Bmocz Schemes For Non-Coherent Wireless Communication, Anthony Joseph Perre

Theses and Dissertations

Non-coherent communication has emerged as a promising approach to address several challenges at the physical layer. A particular scheme called binary modulation on conjugate-reciprocal zeros (BMOCZ) uses the zeros (i.e, roots) of a polynomial to convey information bits. In this thesis, we strive to improve the reliability of BMOCZ in various scenarios. In particular, we utilize machine learning (ML) methods to determine the parameters for BMOCZ and improve upon the decoding performance. Moreover, we introduce a smooshed BMOCZ variant to combat typical impairments encountered within wireless communications, including timing offsets (TOs) for noncoherent orthogonal frequency division multiplexing (OFDM). Through numerical …

Multi-Layer Decision Making For Long-Term Autonomous Mission Based On Dual Process Theory, Shruti Jadhav

Theses and Dissertations

Unmanned aerial vehicles (UAVs) are increasingly used in precision agriculture, where extended autonomous operation is required for monitoring, intervention, and field management. However, achieving long-term autonomy remains challenging due to battery constraints, environmental uncertainty, and the need to balance exploration with event-driven tasks. To address these challenges, a multi-layer decision-making framework inspired by Dual Process Theory (DPT) is developed. The framework combines reactive return-tobase strategies, exploratory navigation, and directional bias from prior missions, with a conflict-monitoring mechanism that adapts system behavior based on real-time conditions. The approach is implemented in a simulated agricultural grid environment, demonstrating improved adaptability and coverage …

Reduced Order Simulator Of A Nuclear Thermal Propulsion System, Jackson Taylor Zazzaro

Theses and Dissertations

This thesis presents the development of a reduced-order simulator for a nuclear thermal propulsion (NTP) system, designed to capture the key thermo-fluid and performance characteristics of such systems while maintaining computational efficiency. The primary objective of this work is to develop and demonstrate a modular simulation framework capable of modeling the coupled physics of an NTP reactor, nozzle, and orbital transfer system. The simulator integrates a reduced-order thermal-fluid model of the reactor, a simplified nozzle model, and an orbital transfer model, providing a comprehensive yet computationally efficient representation of the propulsion process. By employing reduced-order modeling techniques, the simulator achieves …

Rate-Dependent Interlaminar Shear Characterization In Solid-State Extruded Ultrahigh Molecular Weight Polyethylene Film Composites, Frank David Thomas Jr.

Theses and Dissertations

Ultrahigh Molecular Weight Polyethylene (UHMWPE) cross-ply [0o/90o] thin film composites are emerging as an effective material for impact applications due to their high axial strength-to-weight ratio and favorable delamination properties. Mode-II interlaminar shear (ILS) fracture-driven delamination has been shown to be a significant energy absorption mechanism. Therefore, accurately characterizing ILS behavior as a function of strain rate in these composites is essential to inform computational models. Since these composites are significantly thinner and weaker in both interlaminar shear and transverse tension than traditional carbon fiber epoxy composites, standard ILS Mode II test methods/specimens such as end-notched flexure (ENF) are expected …

Enhancing Two-Phase Heat Spreading: Development And Performance Evaluation Of Hermetically Sealed Hybrid Heat Sinks, Walker Ryan Champion

Theses and Dissertations

Modern, high-performance technology presents challenges for thermal management based on power density. To cool heat fluxes to this degree, conventional liquid-cooled heat sinks are utilized because air cooling becomes insufficient (>100 𝑊/𝑐𝑚² ). This study introduces a hybrid heat sink that integrates liquid cooling with a dropwise-enhanced vapor chamber, contains a hermetic seal, and achieves high thermal performance with low energy consumption. The temperature hotspots, thermal resistances, gravitational/pin effects, temperature uniformity, and coefficient of performance were investigated. Experimental results demonstrate a high cooling capacity of 600 W over a 6.25 𝑐𝑚² heating area with a low cooling …

Compost Grinder For The University Of South Carolina Office Of Sustainability, Rori E. Pumphrey, Grace Yaegel, Aaron R. Sawyer, Bradley White

Senior Theses

This project originates from a collaboration with the USC Office of Sustainability, which seeks to improve the handling and processing of food waste generated on campus. The primary challenge is the difficulty in composting certain types of food waste, such as avocado pits, pumpkin rinds, and other dense or fibrous organic materials that are not easily broken down using conventional methods. Existing commercial solutions are often too large and expensive, or electrically powered, and are thus not well suited for the volume or nature of USC's food waste. To address these limitations, our team designed a manually operated food waste …

Determination Of Tensile Strength Distribution Of Single Carbon Fibers At Microscale Gagelengths, Karan Deepak Shah

Theses and Dissertations

High performance carbon fibers are widely used as reinforcements in composite material systems for aerospace, automotive, and defense applications. The tensile strength of commercial fibers is significantly less than its theoretical limits. The composite systems are often overdesigned, thus any increase in the fiber tensile strength can yield significant cost and weight savings. Modification of fiber surface treatment (sizing) during manufacturing is a potential route to enhance fiber strength. Single fiber tensile testing at millimeter-scale is typically used to characterize the effect of sizing on the fiber strength. However, the longitudinal tensile failure of a composite system is a result …

Polymorphism Crystal Structure Prediction With Adaptive Space Group Diversity Control, Sadman Saadeed Omee, Lai Wei, Jianjun Hu

Faculty Publications

Crystalline materials can form different structural arrangements (i.e., polymorphs) with the same chemical composition, exhibiting distinct physical properties depending on how they are synthesized or the conditions under which they operate. For example, carbon can exist as graphite (soft, conductive) or diamond (hard, insulating). Computational methods that can predict these polymorphs are vital in materials science, which help understand stability relationships, guide synthesis efforts, and discover new materials with desired properties without extensive trial-and-error experimentation. However, effective crystal structure prediction (CSP) algorithms for inorganic polymorph structures remain limited. ParetoCSP2 is proposed, a multi-objective genetic algorithm for polymorphism CSP that incorporates …

Machine-Learning-Assisted Discovery Of Lattice Dynamics Signatures Of Sodium Superionic Conductors, Ogheneyoma Aghoghovbia, Riccardo Rurali, Mohammed Al-Fahdi, Joshua Ojih, De-En Jiang, Ming Hu

Faculty Publications

Sodium superionic conductors are key to the development of all-solid-state sodium batteries. Discovery of new superionic conductors has traditionally relied on insights from material defect chemistry and the transition/hopping theory, while the role of lattice vibrations, i.e., phonons, remains underexplored. We identify key lattice dynamics signatures that govern ionic conductivity by analyzing the phonon mean squared displacement (MSD) of Na+ ions. By high-throughput screening of a dataset of 3903 Na-containing structures, we establish a strong positive correlation between phonon MSD and diffusion coefficients, providing a quantitative correlation between lattice dynamics and ion transport. To accelerate this discovery, we incorporate …

Fluorinated Electrolytes For Lithium–Sulfur And Beyond-Lithium Metal–Sulfur Batteries, Avinash Raulo, Saheed Lateef, Hunter Mcray, Kaushek Rahul Ilancheran, Fabio Albano, Golareh Jalilvand

Faculty Publications

Metal–sulfur batteries, particularly lithium–sulfur (Li–S) systems, have attracted significant attention due to their high theoretical energy densities, low cost, and sustainability benefits arising from sulfur’s abundance and non-toxicity. Despite extensive research, their practical deployment remains limited by persistent challenges such as polysulfide shuttling and metal anode degradation, which collectively lead to poor coulombic efficiency and limited cycle life. These issues are further intensified in emerging systems employing sodium, potassium, magnesium, calcium, and siliconbased anodes. Fluorinated electrolytes have emerged as a promising approach to address these limitations. Fluorination enhances oxidative stability, suppresses polysulfide dissolution, promotes stable solid–electrolyte interphase (SEI) formation, and …

Navigating Barriers: Examining Social Equality Through Transportation Disadvantages And Perceived Healthcare Accessibility In South Carolina, Yihong Ning, Songyuan Deng, Yuche Chen

Faculty Publications

Transportation inequities significantly contribute to health disparities, particularly in socially and geographically diverse regions like South Carolina. Prior research predominantly relied on objective measurements, like travel time or distance, to assess healthcare accessibility. However, limited attention has been given to the subjective perceptions of transportation barriers. To address this gap, we designed a comprehensive survey consisting of 61 questions (including 32 five-point Likert-scale items) capturing demographic, socioeconomic, and travel behavior data from a diverse sample of South Carolina residents. Urban and rural contexts were distinguished using county categorization and built environment measures. Exploratory Factor Analysis (EFA) was employed to identify …

Exploring Different Metal-Oxide Cathode Materials For Structural Lithium-Ion Batteries Using Dip-Coating, David Petrushenko, Thomas Burns, Paul Ziehl, Ralph E. White, Paul T. Coman

Faculty Publications

In this study, a selection of active materials were coated onto commercially available intermediate modulus carbon fibers to form and analyze the performance of novel composite cathodes for structural power composites. Various slurries containing polyvinylidene fluoride (PVDF), active material powders, 1-methyl-2-pyrrolidone (NMP) and carbon black (CB) were used to coat carbon fiber tows by immersion. Four active materials—lithium cobalt oxide (LCO), lithium iron phosphate (LFP), lithium nickel manganese cobalt oxide (NMC), and lithium nickel cobalt aluminum oxide (NCA)—were individually tested to assess their electrochemical reversibility. The cells were prepared with a polymer separator and liquid electrolytes and assembled in 2025-coin …

Integrated Algorithm And Hardware Design For Hybrid Neuromorphic Systems, James Seekings, Mahsa Ardakani, Peyton Chandarana, Arshia Eslami, Mohammadreza Mohammadi, Ramtin Zand

Faculty Publications

This paper investigates the combined potential of neuromorphic and edge computing to develop a flexible machine learning (ML) system designed for processing data from dynamic vision sensors. We build and train hybrid models that integrate spiking neural networks (SNNs) and artificial neural networks (ANNs) using the PyTorch and Lava frameworks. We explore the effects of quantization on ANN models to assess its impact on both accuracy and energy efficiency. Additionally, we address the challenges of deploying hybrid models on hardware by implementing individual components on specific edge platforms. We also propose an accumulator circuit to bridge the spiking and non-spiking …

Curved Confinement Directs Anchoring-Mediated Structural Transitions In Highly Chiral Liquid Crystal Shells, Sepideh Norouzi, Jeremy Money, Stiven Villada-Gil, José Martínez-Gonález, Monirosadat Sadati

Faculty Publications

Cholesteric liquid crystals (CLCs) confined in curved geometries exhibit a rich spectrum of defectmediated morphologies governed by the interplay between chirality, curvature, surface anchoring, and confinement. This study systematically investigates structural transitions in highly chiral CLC shells under asymmetric anchoring conditions, focusing on the effects of shell thickness and curvature on pitch axis reorientation and defect formation. Utilizing microfluidic techniques, we generate core–shell droplets with independently tunable anchoring at inner and outer aqueous interfaces. Transitioning from planar–planar to planar-homeotropic boundary conditions via surfactant-mediated modulation induces profound reorganizations in the director field, giving rise to focal conic domains (FCDs), stripe patterns, …

Modeling The Influence Of Silicon Content On Electrochemical Performance Of Silicon-Graphite Blended Electrodes Considering Voltage Hysteresis, Mohamed Atwair, Paul T. Coman, Ralph E. White

Faculty Publications

Silicon, with its high specific capacity, is a highly promising material for lithium-ion battery anodes. To enhance durability, it is commonly combined with graphite in composite anodes. Despite this, the electrochemical dynamics between silicon and graphite are not yet fully understood. Modeling serves as an important tool for analyzing and improving batteries, but current models lack comprehensive representation of the coupled electrochemical and structural behavior of silicon-graphite blended electrodes. Herein, we present a comprehensive model for blended Si/Gr electrodes that incorporates the distinct properties and kinetics of each material. Our approach accounts for the dependence of electrode thickness and solid …

Modeling Self-Discharge In Li/S Batteries Through Electrochemical Anode Reactions: A Theoretical Perspective, Ralph E. White, Paul T. Coman

Faculty Publications

The growing demand for high-energy-density batteries has renewed interest in lithium–sulfur (Li/S) systems, which offer significant advantages but suffer from severe self-discharge during rest. While prior studies attribute this degradation to chemical parasitic reactions or polysulfide shuttling, they overlook the inherently electrochemical nature of anode-side processes. In this work, a 1D physics-based model of a Li/S battery was developed to explicitly incorporate lithium-metal oxidation and the stepwise electrochemical reduction of polysulfides at the anode. Using COMSOL Multiphysics, galvanostatic discharge followed by open-circuit rest under two conditions was analyzed - with and without parasitic anode reactions. The results show that when …

Quantifying Electrokinetics Of Naca0.6V6O163h2O Cathode In Aqueous Zinc-Ion Batteries With Znso4 Electrolyte, Shichen Sun, Boyu Wang, Kevin Huang

Faculty Publications

Aqueous zinc-ion batteries (AZIBs) have been actively studied in recent years as a promising solution for next-generation stationary energy storage due to their inherent safety, low cost, and high energy density. However, their practical deployment remains hindered by the limited cycling stability of cathode materials. Overcoming this challenge requires a detailed understanding of cathodic electrokinetics and degradation mechanisms. In this study, we investigate the electrokinetic behavior of a NaCa_0.6V₆O₁₆3H₂O (NaCaVO) cathode in ZnSO4 electrolyte through a combined application of the galvanostatic intermittent titration technique (GITT) and electrochemical impedance spectroscopy (EIS). For the …

Quantifying Electrokinetics Of Naca0.6V6O16·3h2O Cathode In Aqueous Zinc-Ion Batteries With Znso4 Electrolyte, Shichen Sun, Boyu Wang, Kevin Huang

Faculty Publications

Aqueous zinc-ion batteries (AZIBs) have been actively studied in recent years as a promising solution for next-generation stationary energy storage due to their inherent safety, low cost, and high energy density. However, their practical deployment remains hindered by the limited cycling stability of cathode materials. Overcoming this challenge requires a detailed understanding of cathodic electrokinetics and degradation mechanisms. In this study, we investigate the electrokinetic behavior of a NaCa_0.6V₆O₁₆·3H₂O  (NaCaVO) cathode in ZnSO₄ electrolyte through a combined application of the galvanostatic intermittent titration technique (GITT) and electrochemical impedance spectroscopy (EIS). For …

A Perovskite Nanocomposite And Self-Assembled Nanoparticle-Decorated Cathode For Low Temperature Sofcs, Chunyang Yang, Guoan Wang, Xingjian Xue

Faculty Publications

One-pot route synthesis of an A-site Sm-doped simple perovskite with nominal composition Sm_0.10Ba_0.90Co_0.8Fe_0.2O_3−δ leads to a novel perovskite nanocomposite containing ∼90% A-site cation deficient cubic simple perovskite Ba0.925(Co/Fe)0.962Sm0.038O_3−δ and ∼10% orthorhombic layered perovskite SmBa(Co/Fe)₂O_5+δ. The synergy of the two phases in the nanocomposite results in high electrochemical kinetic properties at low temperatures. With the novel perovskite nanocomposite, a surface nanoparticle-decorated nanocomposite cathode is self-assembled through a one-step sintering process. The corresponding anode-supported cell delivers a peak power density of 1271 mW cm^{−2 …}

Predicting Sleep And Sleep Stage In Children Using Actigraphy And Heartrate Via A Long Short-Term Memory Deep Learning Algorithm: A Performance Evaluation, Robert Weaver Med, Phd, James White, Olivia Finnegan, Hongpeng Yang, Zifei Zhong, Keagan Kiely, Catherine Jones, Yan Tong, Srihari Nelakuditi, Rahul Ghosal, David E. Brown, Russell R. Pate Ph.D., Gregory J. Welk, Massimiliano De Zambotti, Yuan Wang, Sarah Burkart, Elizabeth L. Adams Phd, Bridget Armstrong, Michael Beets Med, Mph, Phd

Faculty Publications

Children's ambulatory sleep is commonly measured via actigraphy. However, traditional actigraphy measured sleep (e.g., Sadeh algorithm) struggles to predict wake (i.e., specificity, values typically < 70) and cannot predict sleep stages. Long short-term memory (LSTM) is a machine learning algorithm that may address these deficiencies. This study evaluated the agreement of LSTM sleep estimates from actigraphy and heartrate (HR) data with polysomnography (PSG). Children (N = 238, 5–12 years,52.8% male, 50% Black 31.9% White) participated in an overnight laboratory polysomnography. Participants were referred be-cause of suspected sleep disruptions. Children wore an ActiGraph GT9X accelerometer and two of three consumer wearables(i.e., Apple Watch Series 7, Fitbit Sense, Garmin Vivoactive 4) on their non-dominant wrist during the polysomnogram. LSTM estimated sleep versus wake and sleep stage (wake, not-REM, REM) using raw actigraphy and HR data for each 30-s epoch. Logistic regression and random forest were also estimated as a benchmark for performance with which to compare the LSTM results. A 10-fold cross-validation technique was employed, and confusion matrices were constructed. Sensitivity and specificity were calculated to assess the agreement between research-grade and consumer wearables with the criterion polysomnography. For sleep versus wake classification, LSTM outperformed logistic regression and random forest with accuracy ranging from 94.1to 95.1, sensitivity ranging from 94.9 to 95.9 across different devices, and specificity ranging from 84.5 to 89.6. The addition of HR improved the prediction of sleep stages but not binary sleep versus wake. LSTM is promising for predicting sleep and sleep staging from actigraphy data, and HR may improve sleep stage prediction.

Machine Tool Interoperability In Smart Manufacturing And Industry 4.0, M. R. Mccormick, Mohammed Shafae, Thorsten Wuest

Faculty Publications

Real-time decision making is supported by data-hungry emerging technologies such as machine learning and digital twins. Innovations in manufacturing process control utilizing these technologies are constrained by interoperability. Marketing materials, sales pitches, and academic literature portray interoperability on the factory floor as seamless and robust. However, this study demonstrates that in spite of plentiful mature standards, interoperability on the factory floor is neither seamless nor robust. To exemplify interoperability in the context of an established and widely adopted standard, this study analyzes the interoperability of machine tools produced by a premier equipment builder which has exceeded US$1 billion in sales …