Melts To Solutions: Structure, Dynamics, And Response Of Polyelectrolytes, Shalika Meedin

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The current research elucidates the changes in the structure and motion of polyelectrolytes as they are perturbed by solvents and shear flows. Polyelectrolytes are macromolecules whose backbone consists of long, predominantly hydrocarbon chains, substituted by ionizable groups, which tend to dissociate into ions in polar solvents. Their properties result from a delicate balance of elastic energy that arises from the polymeric backbone and electrostatic forces, which stem from the ionizable groups. Though polyelectrolytes have an immense potential to propel numerous technologies, from clean energy to drug delivery systems, understanding the delicate balance between the properties of the polymer backbone and …

Accurate Temporal Integration Schemes For Nonlinear Adsorption Problems, Evan D. Butterworth

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We consider a nonlinear transport problem to model the chromatography process of high-capacity multimodal membranes. Robust and efficient algorithms that simulate these bioseparation processes are critical to developing therapeutics for various chronic illnesses and infectious diseases. However, much of the current methodology focuses on stabilization and linearization techniques, often implementing low-order time-discretizations and linearized adsorption, resulting in inefficiencies and inaccuracies in the numerical solution. Utilizing Rothe's method, we develop various time-discretization schemes coupled with the finite element method to solve the fully implicit problems. Stability and solvability results are presented for several methods. Through multiple high-level software implementations paired with …

Exploring The Impact Of Co-Teaching On High School Math Achievement For Students With Disabilities, Josh T. Oxendine

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This Dissertation in Practice explores the implementation of a co-teaching model in Algebra 1 classrooms at Green High School, part of the Excellent School District. The study was conducted due to the persistent underperformance among students with disabilities (SWD) on the Algebra 1 End of Course test, which led to the school’s designation as an Additional Targeted Support and Improvement (ATSI) site by the South Carolina Department of Education. Developed using the principles of improvement science, the study utilized the Plan-Do-Study-Act (PDSA) cycle as a framework to guide and evaluate change.

The change idea centered on embedding co-teaching in two …

Culturally Relevant Pedagogy In Undergraduate General Chemistry, Destinee J. Cooper

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General chemistry is a foundational course for advancement in most undergraduate STEM programs, but unfortunately, many students do not continue in STEM after their experiences in their general chemistry course. Culturally relevant pedagogy (CRP) has the potential to increase students’ positive experiences in general chemistry by centering their needs, identities, and backgrounds. However, this pedagogical approach has not been widely studied in the college general chemistry context. As such, my four-paper dissertation broadly aimed to explore both the implementation and outcomes of CRP in undergraduate general chemistry.

The first paper reviewed the literature on culture-based pedagogies across the full undergraduate …

Towards Securing Ai Systems: Investigating Threats In Multimodal Autonomous Driving & Rag Systems, Saket Sanjeev Chaturvedi

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Artificial Intelligence (AI) systems have become central to high-stakes applications such as autonomous driving and language-based decision support. As their deployment accelerates, ensuring the security and trustworthiness of these systems becomes paramount. Among the most stealthy and potent threats are backdoor attacks, where models behave as expected under normal conditions but exhibit malicious behavior when triggered by specific inputs, either digital or physical.

This thesis investigates novel backdoor and adversarial vulnerabilities across two emerging classes of AI architectures: (1) multimodal 3D object detection systems that fuse LiDAR and camera data, and (2) Retrieval-Augmented Generation (RAG) systems that pair large language …

Constructing Code-Based Zero-Knowledge Proofs Leveraging Generic Errors And Bounded Vectors, Freeman Slaughter

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Quantum computing is developing at an expeditious rate, and once fully scalable quantum computers become realized, classical cryptographic systems face obsolescence. This approaching peril has prompted a paradigm shift away from pre-quantum cryptography and towards post-quantum primitives, such as those that arise from the field of coding theory. Among these, zero-knowledge proofs have emerged as a dynamic tool instrumental in constructing quantum-resilient digital signature schemes.

We being by introducing HammR, a pre-quantum zero-knowledge proof protocol designed to verify Hamming weight and entry constraints of error vectors, and comprehensively establish its security. Subsequently, we extend HammR to the multi-party computation setting, …

Teacher Efficacy In Reading Intervention: The Role Of Coaching And Professional Development In Foundational Literacy, Susan S. Chapman

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This Dissertation in Practice utilized improvement science methods to increase teacher self-efficacy in foundational reading practices and to address the oral reading fluency (ORF) challenges of elementary students who consistently score below proficiency. Rooted in Bandura’s theory of self-efficacy and the Active View of Reading, the study aimed to build teacher confidence in delivering foundational reading instruction while improving student ORF rates. A Plan-Do-Study-Act (PDSA) cycle was implemented with second-grade teachers and targeted the following aim: increase ORF by 12 words correct per minute (wcpm) for students receiving Tier 3 intervention over an eight-week cycle. Coaching, using the student-centered coaching …

Are They Ready? Impacting Kindergarten Readiness Through The Science Of Reading, Traci T. Boyles

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The purpose of this research study was to investigate how Science of Reading (SOR) professional development for preschool teachers, implemented through collaborative teaching and assessment cycles, influences the kindergarten readiness of preschool students.

Students from impoverished families start kindergarten at a considerable disadvantage regarding literacy. Literacy-focused curricula and professional development for teachers strongly affect reading outcomes. Multi-Tiered Systems of Support (MTSS) provides a systemic framework for data-based problem solving and decision-making. The MTSS framework aligns literacy interventions with tiered supports to ensure all students receive the assistance they need to achieve reading proficiency.

The South Carolina Child Early Reading Development …

Online Multiobjective Optimization, Kristen Joyce

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Online optimization (OO) is an iterative process of decision making under uncertainty. At every step, a decision is made before the outcome of this decision is known. For the online optimization model, the objective function is unknown at the time the decision is being made. It is very likely that the taken decision is not optimal, so the decision maker incurs a loss, called regret, in every iteration. The goal of the online optimization algorithm is to compute a decision at every step so that the overall regret cost is minimized. In particular, the average regret produced by an ideal …

Empowering Employability: Voices Of Black Women Leveraging Community Cultural Wealth In An Undergraduate Agricultural Program, Rose Marie Somers

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Across the nation, agricultural industry professionals have bemoaned the shortage of qualified professionals, expressing an expanding need for graduates with a blend of discipline-specific and employability skills to advance the sector. Research indicates that the future of the US agriculture sector hinges on a diverse and skilled workforce. Yet, a paucity of literature exists on Black women's enduring legacy, experiences, and how they understand and develop 21st-century critical transferable professional competencies needed to address complex challenges in modern agriculture. Black women have a long tradition in agriculture and a wealth of cultural knowledge, skills and innovations that are untapped. This …

Sensitivity Analysis Of Flexible Pavement For South Carolina Conditions, Shilpa Girish

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The objective of the study was to evaluate the sensitivity of various input variables on the flexible pavement design thickness of high-speed, high-traffic routes in South Carolina using the Mechanistic-Empirical Pavement Design Guide (MEPDG) by means of the AASHTOWare Pavement ME Design software using global calibration coefficients with a focus on bottom-up fatigue cracking. The variables considered in this investigation included two-way average annual daily truck traffic (AADTT), asphalt mix type, climate station, subgrade type and resilient modulus, and aggregate base thickness. The study includes comparative analysis using older methods like the AASHTO 1993 method and the South Carolina DOT …

Chemical & Electromagnetic Signatures Of Binary Neutron Star Mergers, Benjamin Amend

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Binary neutron star (BNS) mergers are some of the most energetic events in the universe, producing both short gamma-ray bursts (GRBs) and kilonovae. GRBs are brief, bright flashes of gamma rays, powered by ultra-relativistic jets launched during the merger. These jets produce a prompt burst of gamma rays, followed by a broadband afterglow generated by external shocks as the outflow interacts with the surrounding medium. Kilonovae are optical-infrared transients from the radioactive decay of heavy, neutron-rich nuclei formed through the rapid neutron capture process (r-process) in the merger ejecta. Together, GRBs and kilonovae provide unique laboratories for probing fundamental physics …

Robust Online Inertia Estimation In Power Systems Using Ambient Data In The Presence Of Inverter-Based Resources, Narges Ghiasi

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The increasing penetration of Inverter-Based Resources (IBRs) in power systems has significantly altered system dynamics, reducing the system's effective rotational inertia and challenging frequency stability. Accurate online inertia estimation is essential for maintaining system reliability under these evolving conditions. This paper introduces a robust methodology for online inertia estimation using ambient data collected during normal system operation. The proposed method employs a state-space model to represent system dynamics and introduces synthetic step changes to simulate disturbances. By analyzing the frequency response and applying advanced signal processing techniques, the methodology estimates system inertia without requiring real large-scale disturbances. The approach is …

Replacement Optimization For Offshore Wind Turbine Farms, Morteza Soltani

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This dissertation is concerned with devising optimal replacement policies for offshore wind turbines with a focus on minimizing the costs associated with major component replacements and production losses due to downtime. Like their onshore counterparts, offshore wind turbines are subject to progressive degradation due to normal operations, as well as the influence of dynamic environmental conditions that influence their rate of degradation. Due to their proximity, wind farm turbines share common environmental conditions, as well as specialized maintenance resources. Their common exposure to the environment and need to share resources introduce both stochastic and economic dependence between the wind turbines. …

Engaging Minds: The Impact Of Multimodal Instruction On Multiplication Facts, Ashleigh Cobey

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This dissertation examined the impact of a multimodal, station-based instructional approach on student engagement and multiplication fact fluency among third-grade students at Hopeful Elementary School (HES), a Title I, high-poverty school. Traditional methods of rote memorization have not consistently met the needs of all learners, particularly those from under-resourced backgrounds or with disabilities. This study explored how structured opportunities to practice multiplication through music-based, game-based, and technology-enhanced learning experiences influenced student engagement and fluency.

Using a multimethod design, the intervention group participated in the Multimodal Multiplication Intervention, rotating through three stations Monday through Wednesday and selecting a preferred station on …

Studying The Impact Of Co-Teaching On Students With Disabilities Self-Efficacy In An Algebra 1 Course., Shannon E. Sharkey

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ABSTRACT

Students with disabilities (SWD) at Large High School in Rural School District have consistently underperformed in Algebra 1 as compared to their non-disabled peers and SWD across South Carolina. This performance gap contributes to the school’s designation as an Additional Targeted Support and Improvement (ATSI) site, putting it at risk for state intervention. This dissertation investigates whether implementing a co-teaching model in Algebra 1 can positively impact SWD students’ self-efficacy in mathematics, with a secondary focus on potential gains in academic performance in Algebra 1 on the state End of Course (EOC).

Grounded in improvement science methodology, the study …

Improving Retention Of Students With Disabilities In Stem Through Math-Based Type Science Readiness, Eleni N. Koukoularis

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Abstract

This Dissertation in Practice examined the impact of a Math for Science Readiness (MSR) intervention on the science course planning behaviors of Students with Disabilities (SWD) in College Preparatory Basic (CPB) Chemistry, with the aim of increasing enrollment into Physics 1 College Placed Academic (CPA). Using an approach grounded in sociocultural theory and strength-based practices, the intervention implemented 16 short modules connecting chemistry and physics through shared math themes to reinforce math concepts across disciplines.

Data collected included physics interest surveys, common assessment exam scores, enrollment data, and counselor feedback to evaluate whether targeted math support could promote progression …

From Collaboration To Achievement: Exploring Co-Teaching As A Strategy To Close The Gap In Mathematics For Students With Disabilities, Lindsay L. Stewart

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This study addressed the persistent achievement gap in Algebra 1 for students with disabilities (SWD) at Popular High School (PHS), a rural high school within Sweet County School District (SCSD). In response to historical underperformance on the South Carolina Algebra 1 End-of-Course (EOC) assessment and the school’s designation for Additional Targeted Support and Improvement (ATSI), the district piloted a co-teaching intervention to provide more inclusive and supportive instruction for SWD. In this context, co-teaching refers to a collaborative instructional model in which a general education and a special education teacher share responsibility for planning, delivering, and assessing instruction in the …

Toward A Unified Theory Of Fire-Induced Spalling Of Concrete: Transcending Domain Knowledge Limitations Through Explainable Artificial Intelligence, Causal Discovery And Inference, Mohammad Al Bashiti

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When concrete is exposed to fire, it can suddenly break apart in a dangerous process called spalling. This can severely weaken buildings and even trigger a collapse. While researchers have studied this problem for years, we still don’t fully understand what causes it. My research uses a combination of data, and advanced AI techniques to identify and quantify the key factors that increase the risk of spalling. I collected data from over 1,000 fire tests and used AI models to predict when spalling might happen. I also applied explainable AI tools to understand why it happens.

The results showed that …

Discovering High-Redshift Bl Lacs And Localizing Grbs For Mev Missions, Yong Sheng

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Blazars are active galactic nuclei (AGNs) with their jets aligned towards Earth. Gamma-ray bursts (GRBs) can be classified into long and short types. Long GRBs are produced by the collapse of massive stars, while short GRBs are formed by binary mergers (neutron star - neutron star or neutron star - black hole mergers). Both objects are the key probes of extreme physics processes and cosmic evolution, providing us an unique window to understand the Universe. My research aims to measure the redshift of blazars and localize GRBs for proposed and upcoming gamma-ray telescopes. BL Lac objects (BL Lacs) are a …

12co Ro-Vibrational Spectroscopy Of Protoplanetary Disks: Inferring Planet-Disk Interactions, Janus Kozdon

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Observing and studying planets around young stars during their initial formation stages is essential for understanding the physics of their formation. Protoplanetary disks are the host sites of planets, and they exhibit substructures that hint towards the planets' presence, but the planet itself has rarely been detected. Analysis of the substructures in protoplanetary disks, especially towards the inner regions where most planets seem to lie, will provide information that can be used to refine theories about planet-disk interactions and, ultimately, planet formation. To probe the high-velocity inner regions, this study utilizes high-resolution spectroscopy, which has increased sensitivity with increasing velocities. …

Investigation Of Solid-State Reactive Sintering And Rapid Laser Reactive Sintering For Al-Doped Li7la3zr2o12 Solid-State Electrolyte, Aaron Santomauro

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As a society, we’ve exhausted an extreme amount of fossil fuels and put an overwhelming strain on Earth’s natural resources. From this, it is critical to think about the successful future of our planet and ourselves by developing energy devices such as all-solid-state lithium-ion batteries (ASSLIBs). These devices offer a greener and more efficient alternative to power our daily lives, such as electric vehicles (EVs), portable electronics, medical devices, grid-scale energy storage, and aerospace/aviation. ASSLIBs are an excellent alternative to liquid-state batteries, which pose dangerous safety concerns (e.g., flammability, electrolyte leakage, etc.). These ASSLIBs are known to have generally high …

Experimental Design And Analysis For Decision Making: Methodology And Applications, Yezhuo Li

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This dissertation develops and applies advanced statistical and optimization frameworks to enhance decision-making under uncertainty, particularly in engineering and manufacturing contexts. First, we introduce an approach for the optimal design of controlled experiments that accounts for observational covariates, enabling more precise and personalized decisions. Second, we explore the application of constrained Bayesian optimization, using Gaussian process surrogate models, to optimize composite cure processes, significantly reducing computational effort while maintaining high predictive accuracy. Building on this foundation, we extend Bayesian optimization to bivariate Gaussian process models that capture correlations between objective and constraint functions, offering new insights into multidimensional decision landscapes. …

Advancing Lithium-Ion Batteries Through Exploration Of Novel Physico-Chemical Phenomena, Peshal Karki

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Lithium-ion batteries (LIBs) power a wide range of modern devices, from smartphones to electric vehicles. This dissertation integrates materials characterization and electrochemical testing to develop novel Si-based electrode materials, investigate separator effects, and improve electrochemical impedance spectroscopy (EIS) modeling. First, I synthesized Si@CC composites using bio-based carbon sources and discovered a novel in situ disorder reduction in the amorphous carbon cloud during cycling, attributed to Si volume fluctuations and mesoporous carbon structure, which enhanced capacity retention. A binder-free electrode (Si@CC@BP) using bucky paper further improved gravimetric and areal capacities while reducing weight and manufacturing complexity.

Next, I investigated how separator …

Structural Design Using Conditional-Gan Fused With Property Text Information: A Case For Masonry Structures, Arash Teymori Gharah Tapeh

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Structural design, by nature, is a complex process that requires a considerable amount of time, expertise, and knowledge. In such a process, the structural designer must navigate various codal provisions to crystallize a proper and adequate design. As the role of automation continues to shape the domain of structural engineering over the past few decades, a new front leverages artificial intelligence (AI). Currently, AI acts as a "copilot," collaborating to advance workflow speed and accelerate the design process. Among all the different collaborations between humans and AI, GANs (Generative Adversarial Networks) are seen to complement human creativity by automating specific …

Tiered Structured Intervention Program To Prevent Student Pushout In High School, Toshawnka T. Mahone

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High school dropouts remain a challenge in the United States Educational System, particularly among students impacted by chronic attendance issues, academic struggles and persistent behavioral issues. This Dissertation in Practice (DIP) examines the implementation of ELEVATE3, an intervention program designed to prevent student pushout by addressing distinct at-risk factors: attendance, behavior and academic retention. Framed by pushout theory and grounded in goal-setting and self-efficacy literature, this study investigates how targeted structured supports influence students' motivation, academic achievement, and self-regulation. This mixed-methods research used student academic records and staff interviews to determine the impact on a rural Title 1 high school. …

Decoding The Mobile App Playbook: How Sdks And Cross-Promotions Drive Market Performance, Pranith Abbaraju

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This dissertation investigates the strategic determinants of mobile app success within the evolving mobile platform ecosystem, focusing on app development choices and user acquisition strategies. Drawing on large-scale longitudinal data from the iOS platform, the research comprises two empirical studies contributing to the literature on digital platforms, modular design, and mobile advertising.

The first study examines how the integration of software development kits (SDKs)—a central mechanism of modular innovation—affects app market performance. The analysis identifies SDK popularity as a dual-edged strategic attribute. While popular SDKs can enhance app quality by enabling access to reliable, widely adopted functionalities, their widespread adoption …

Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan

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A dissertation is proposed to explore human comfort in human-robot collaboration (HRC) through modeling, prediction, and enhancement methodologies. Human comfort is a crucial yet underexplored factor in HRC, directly influencing task efficiency, trust, and overall collaboration effectiveness. Understanding the influential factors, developing computational models, and refining methods to improve human comfort in HRC are essential steps toward advancing the field of collaborative robotics. To address these challenges, multiple studies have been conducted. A series of experimental studies were performed to investigate how robot motion-based parameters affect human comfort in HRC. These studies examined both analytical comfort modeling approaches and physiological …

Three Essays In The Economics Of Disagreements: Incentives, Measurement And Persistence, Mustafa W. Alam

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This dissertation presents three chapters that contribute to the study of economic forces shaping disagreements in society.

In Chapter 1, I demonstrate that political polarization can intensify due to innovations in the information market even if a population's ideological distribution is fixed. Viewership-maximizing news firms cater to a diverse audience who assess source accuracy using noisy private signals that vary in precision and ideological bias. If better-informed consumers disproportionately migrate to newer platforms for news (e.g., the Internet), traditional media firms increase news slant to appeal more to less-informed partisans on both sides of the ideological spectrum. This leads to …

Bilevel Network Interdiction Models For Human Trafficking Disruption, Daniel Bruno Lopes Da Silva

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In this dissertation, we study a series of bilevel network interdiction problems motivated by applications in human trafficking disruption. First, we consider a bilevel network interdiction problem where the follower aims to maximize the amount of flow from the source node to the sink node and the leader aims to minimize the number of arcs from a critical set that have positive flow on them in the solution obtained by the follower. This problem models the situation where an anti-trafficking agent wants to minimize the number of people affected by the trafficking operations whereas the trafficker wants to maximize trafficking …