Doctoral Dissertations
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- Identifying the psychological, behavioral, and neural effects of dance on young adults with ADHDTasnim, Noor E. (Virginia Tech, 2026-02-03)Attention-deficit/hyperactivity disorder (ADHD) is emerging as a growing public health challenge in the United States. More than 15 million adults in the United States are diagnosed with ADHD in adulthood. Moreover, stimulant refill rates are increasing while patients struggle to get their ADHD medications. Although more adults are seeking help for ADHD, primary care settings continue to fall short of meeting quality-of-care standards for accurate diagnosis and effective treatment. To address this issue, this dissertation set out to accomplish the following aims: 1) Examine the psychological, behavioral, and neural predictors of ADHD symptomatology in young adults and 2) Study the acute effects of dance and exercise on the psychological, behavioral, and neural outcomes of ADHD in this population. For Aim 1) 67 young adults (Ages: 18-24, Sex: Male [N=18], Female [N=49]) completed a series of mental health questionnaires, executive function tasks, and balance assessments while wearing a 64- electrode electroencephalography cap. Depressive symptoms, sex, alpha (8-12 Hz) power in the Right Paracentral Lobule, and P3b Mean Amplitude were the greatest predictors of self-reported symptoms on the Adult ADHD Self-Report Scale v1.1. For Aim 2) 63 of these participants (Sex: Male [N = 17], Female [N = 46]) were assigned, through stratified randomization, to one of three 30-minute interventions associated with a dance exergame: 1) sitting and watching the game, 2) riding a bike to the game, 3) dancing along with/playing the game. Participants underwent the same series of assessments about 1 week after their first visit but underwent their assigned intervention before all assessments took place. Biking and dancing suppressed alpha power in brain regions associated with attentional networks and improved cognitive flexibility. Dance, but not biking, specifically suppressed alpha activity in regions associated with top-down attentional control. The identification of significant neural predictors and nonpharmacological treatment outcomes associated with attention can guide future standards in the diagnosis and treatment of adults with ADHD.
- Understanding the Mechanistic Pathways of Layered Oxide Cathode Synthesis for Sodium-Ion BatteriesPromi, Anika Tabassum (Virginia Tech, 2025-12-16)Sodium-ion batteries (SIBs) offer cost-effective and earth-abundant complementary technology to lithium-based systems, positioning them as promising candidates for large-scale energy storage to meet the world's exponentially growing energy demands. This dissertation investigates the interconnected roles of precursor chemistry, interfacial solid-liquid interactions, and calcination pathways involved in the synthesis of Ni-Fe-Mn –based layered oxide cathodes for sodium-ion batteries. It begins by examining equimolar Ni-Fe-Mn hydroxide precursors synthesized byammonia- and citrate-based co-precipitation routes, comparing their morphological control, stoichiometric accuracy, and structural homogeneity under varying reaction conditions. Motivated by the challenges observed in synthesis, the second study shifts focus to a fundamental investigation of metal–ligand interactions at the solid–liquid interface. Using in-situ synchrotron X-ray fluorescence microscopy and statistical modeling, we quantify how pH and metal identity influence interfacial dissolution-redeposition dynamics of multiple transition metals in alkaline media and reveal metal-specific spatial–temporal trends within multicomponent systems.Subsequent chapters shift focus to the high-temperature solid-state transformation of these precursors into NaNi1/3Fe1/3Mn1/3O2 cathodes. First, we analyze the mechanistic reaction pathway of sodium carbonate-based calcination, identifying key stages of precursor dehydration, major intermediate formation, and grain growth behavior. We then systematically investigate how variations in precursor design route and sodium source influence calcination behavior, demonstrating that structural and morphological differences govern distinct phase evolution pathways, ranging from topotactic transformations to complex multistep transformation. Finally, we extend this methodology to Mn-rich systems for P2-type sodium layered oxides, demonstrating that citrate-based strategies can yield favorable particle morphologies across a range of manganese-rich compositions, despite challenges associated with Mn precipitation. Across these studies, we establish a framework for linking precursor synthesis to downstream calcination outcomes, offering new insights into optimizing reaction parameters for more efficient synthesis of sodium-ion layered oxide cathodes.
- Social Robots for Human Companionship: Stigma Perceptions, Social Orientation, and Design PreferencesAhmed, Iqbal Uddin (Virginia Tech, 2026-03-06)Advances in artificial intelligence (AI) have transformed the capabilities of social robots, enabling them to participate in interactions that resemble human social exchange. Through adaptive learning and personalized engagement, these systems can provide counsel, emotional support, and companionship across a range of social contexts. Individuals perceive the advantages of interacting with a social robot (vs. human) such as being perceived as nonjudgmental, reduced risk of social rejection, accessible, and emotionally responsive interactions. As social robots become increasingly capable of simulating humanlike social presence, these developments raise important questions about the psychological processes that underlie how individuals perceive, evaluate, and adopt social robot as companions. Researchers in marketing, robotics, and computer science have largely focused their attention on facilitating factors that lead to social robot acceptance. Such findings may lead designers to adopt a "one-size-fits-all" perspective. However, far less is known about individual differences in social robot preferences. In addition, the literature is sparse on how social robot designs may influence stigma perceptions. In particular, there is a gap in our understanding of how social robots with anthropomorphic designs may drive inferences of humanlike capabilities, elicit stigma, and the psychological processes by which stigma shapes resistance to social robot companionship. This dissertation examines how social robot design activates psychological mechanisms that influence the adoption of AI-driven social robots for companionship. Essay 1 (Chapter 2) investigates how anthropomorphic design features shape perceptions of a social robot's cognitive, affective, and social capabilities and how these inferences mediate perceived stigma (in parallel). We then investigate a psychological process in which perceived stigma, anticipated stigma, and self-stigma serially mediate adoption intentions for social robots as companions. Essays 2 and 3 address individual differences in social relationship orientations that may signal differential benefits from AI companionship. Drawing on literature in social competence, exclusion, and solitude, Essay 2 (Chapters 3 and 4) develops a scaling methodology that classifies individuals as socially included (I), socially excluded (D), or social excluders (R). Using a multi-stage process, we create and validate a 42-item instrument that distinguishes these social relational profiles. Finally in Essay 3 (Chapter 5) we explore how design preferences for social robots (physical features, anthropomorphic qualities, interactional capabilities, and preferred relational roles) vary by these social relationship profiles. Together, these essays provide a comprehensive framework for understanding how stigma, individual differences, and design considerations may interact and influence the adoption of social robot companions. The dissertation concludes with theoretical, managerial, and policy implications for designing and responsibly deploying AI technologies that support human social needs and address the growing societal challenge of companionship deficits and loneliness.
- Scalable Systems for Machine LearningKhan, Ahmad Faraz (Virginia Tech, 2026-03-06)Federated Learning (FL) enables collaborative model training without centralized data collection, thereby preserving data privacy and reducing data transfer costs. However, deploying FL in resource-constrained distributed environments like Edge and IoT applications introduces significant challenges related to cost, scalability, and efficiency. Traditional cloud-based FL aggregator solutions are resource-inefficient and expensive when applied at the Edge, leading to low scalability and high latency. Additionally, client-side resource heterogeneity results in issues such as stragglers, dropouts, and performance variations, complicating effective client participation. This thesis explores these challenges and presents methodologies and frameworks that enhance the efficiency and scalability of FL systems in resource-constrained environments. First, an adaptive FL aggregator is presented, which is designed specifically for Edge environments, enabling users to manage the trade-off between cost and efficiency. This adaptive aggregator addresses the inefficiencies of cloud-based solutions by improving scalability and reducing latency. Second, we develop FLOAT, a framework that enhances FL client resource awareness by dynamically optimizing resource utilization to meet training deadlines and mitigating stragglers and dropouts through various optimization techniques. FLOAT employs multi-objective Reinforcement Learning with Human Feedback (RLHF) to automate the selection and configuration of these techniques, tailoring them to individual client resource conditions. Third, we design IP-FL, which treats incentivization and personalization in FL as interrelated challenges and solves them with an incentive mechanism that fosters personalized learning. IP-FL allows clients to indicate their cluster membership preferences based on data distribution and incentive-driven feedback without involving the aggregator to preserve privacy. This approach enhances the personalized model appeal for self-aware clients with high-quality data, leading to their active and consistent participation. Lastly, FLStore is proposed as a serverless framework for efficient FL non-training workloads and storage. FLStore unifies the data and compute planes on a serverless cache, enabling locality-aware execution via tailored caching policies to reduce latency and costs compared to cloud-based in-memory and object stores. FLStore integrates seamlessly with existing FL frameworks with minimal modifications, while also being fault-tolerant and highly scalable. Our work aims to contribute toward the development of efficient and scalable machine learning systems suitable for widespread deployment in Edge and IoT applications, addressing the critical challenges of cost, scalability, and efficiency in resource-constrained distributed learning environments.
- Stories of Migration: Investigating Artistic Work to Encourage Social ChangeSoares Souza de Souza, Aline Regina (Virginia Tech, 2026-03-03)This dissertation employed an arts-based research method to encourage shifts in audience member perspectives concerning (im)migration, (un)belonging, space and place. It addressed two central questions: What is the potential of multimedia artistic work to disrupt, unsettle, and transform perceptions and meaning concerning migrants and migration? What art forms can allow the oppressed working class, among others, to transcend de Certeau's sphere of victimization? How can art be politicized by incorporating technology and new media, as argued Walter Benjamin? This exploration matters because art can communicate in ways that words cannot. Overall, I found that visual art, alongside spatialized sound and dance, can transform space on an architectural level, transcending de Certeau's sphere of victimization. I argue that the transformation of space is key to politicizing art, in Benjamin's terms. This type of art provides an experience that affects multiple senses to tell stories. For this dissertation, these were stories of migration. I drew on the work of Walter Benjamin, Herbert Marcuse and Anja Bieri to argue that multimedia art has the potential to encourage audiences to rethink their perceptions of migrants and migration. This work contributes to existing literature by presenting an arts-based research method that uses artist-scholarship in two ways. First, I used social and architecture theory to consider (im)migration and (un)belonging, weaving arguments from multiple authors and fields into a conversation. Second, I used artistic practice founded on premises drawn from the above authors in an iterative process to produce art. With theory and practice together, with one influencing the other, back and forth, I created audiovisual art via a transdisciplinary collaboration, centered on stories of (im)migration and (un)belonging. Art is one way to build empathy and solidarity and to imagine the future. The paintings that appear in this dissertation are separate from the performance art I created for it and meant to supplement that effort by creating spaces in which readers can reflect on otherwise abstract, but cognate, themes such as movement, borders and belonging.
- Enhancing English Language Learning Skills by Using Metaverse Technology: An Integrative Literature ReviewKhayyat, Maram Muneer (Virginia Tech, 2026-03-02)Technology has been developing in ways that can help students learn better, including how they learn languages such as English. The purpose of this study was to analyze prior research on the use of Metaverse Technology (MvT) in educational settings, focusing on studies centered on English as a Foreign Language (EFL) students, for the purpose of enhancing English Language Learning (ELL) skills and formulating guidelines for instructors in Higher Education Institutions (HEIs). The potential of MvT in EFL is that students can practice the English language inside digital spaces that feel real, such as talking, solving problems, or working on group projects together. They can talk, move, and solve problems inside those spaces instead of only reading or listening in a traditional class. This study utilized an integrative literature review (ILR) approach related to how instructors use MvT to enhance EFL skills among students. Further, the study identified how the integration of MvT could address challenges in engaging students and improving their English Language skill proficiencies. The objective of the study was to identify practical, evidence-based ideas that instructors could use to improve student learning. The process involved completing an integrative literature review, which was screened, compared, and grouped by shared themes. The results of this study contribute to instructional design (ID) research, suggesting practical ways that universities and instructors may incorporate MtVs into EFL in Higher Education.
- Integrative Genomic Approaches for Plant Trait Discovery, Fungal Pathogen Identification and TaxonomyBelay, Kassaye Hussen (Virginia Tech, 2026-03-02)Genomics underpins crop improvement and plant health surveillance, yet its application remains constrained by incomplete detection of complex genetic variation, difficulty recovering pathogen genomes directly from diseased tissues, and inconsistent reference resources for fungal and oomycete identification. This dissertation integrates long-read sequencing, metagenomic approaches, and genome-based classification to address these limitations. First, long-read resequencing of 29 food-grade soybean and edamame genotypes enabled discovery of structural variants (SVs) associated with agronomic and seed-quality traits and established a workflow for SV candidate discovery and marker development. Experimental validation confirmed SV-phenotype relationships, including a 1,443-bp deletion between Kunitz trypsin inhibitor (KTI) genes associated with reduced expression and decreased seed KTI content. Second, long-read metagenomic sequencing was applied to vascular streak dieback, an emerging disease of woody ornamentals in the U.S., in contexts where culturing is infeasible. Sequencing of 106 samples from 34 host species across seven states identified Ceratobasidium sp. as the only pathogen consistently detected across samples and made it possible to assemble 17 high-quality genomes. Comparative phylogenomics and pangenome analyses indicated that U.S. isolates form a distinct cluster relative to Ceratobasidium theobromae and revealed gene-content differences, including candidate effectors and secondary metabolite gene clusters, which may contribute to host interaction and support improved diagnostics. Third, this dissertation introduces Myco-genomeRxiv, a web platform implementing an ANI-based Life Identification Number (LIN) system for genome-based identification and strain typing of fungi and oomycetes. Populated with 19,155 genomes from the NCBI Assembly database, the system uses genome-based classification to flag misassigned taxonomic identifiers and likely contamination and circumscribes 17,702 putative species using existing genome membership or a provisional 99% ANI threshold. Collectively, these studies integrate long-read sequencing, metagenomics, and genome-scale classification into a unified framework that expands discovery of trait-associated variation, enables genome-resolved investigation of disease from complex plant samples, and improves the stability and reproducibility of fungal and oomycete taxonomy for agricultural, clinical, and biosecurity applications.
- Fluid and Pressure Dynamics in Natural and Engineered Coastal Aquifer SystemsOgunleye, John Babatunde (Virginia Tech, 2026-03-02)Coastal aquifers are increasingly impacted by groundwater depletion, seawater intrusion, and land subsidence driven by long-term pumping. This dissertation uses 3D numerical modeling to evaluate how variable-density flow and geological heterogeneity influence pressure response, intrusion geometry, and deformation in stressed coastal systems. Three aquifer domains are examined: homogeneous aquifers, confined aquifers with continuous clay layers, and heterogeneous aquifers containing discontinuous clay layers (DCLs). Results show that geology strongly governs intrusion patterns. Homogeneous systems produce broad inland intrusion, continuous clays enhance vertical upconing, and DCLs create irregular and asymmetric intrusion zones. Because seawater is denser and less viscous than freshwater, saltwater cases exhibit larger and more persistent drawdowns, increasing modeled subsidence by 0.2 to 0.5 m after 100 years of pumping. The dissertation also evaluates Managed Aquifer Recharge (MAR) through analysis of the Sustainable Water Initiative for Tomorrow (SWIFT) pilot program in the Virginia Coastal Plain. The Potomac aquifer overlies crystalline basement rock, raising concern about downward pressure propagation in the context of injection-induced seismicity. Ensemble simulations reproducing the 2018 to 2022 pilot injections show that injection rates near 2 million gallons per day may generate pressure increases of approximately 40 kPa in the upper 200 m of the basement, although this response remains localized to within 2 km of the injector. Finally, models incorporating newly identified heterogeneity demonstrate that 20 m thick clay interbeds and laterally extensive DCLs significantly reduce pressure transmission to the basement, improving the stability and safety of MAR operations.
- Design and Synthesis of 8-Trifluoromethyl-Substituted Heterocyclic Small Molecule Mitochondrial Uncouplers for the Treatment of Metabolic DiseasesKrinos, Emily (Virginia Tech, 2026-02-27)
- Developing C–H bond Functionalization, Organocatalytic Hydrophosphination Reactions and Anti-Invasion AgentsGwinn, Reilly (Virginia Tech, 2026-02-27)In chapters 1-3, we will discuss the development of iron alkoxide complexes for C–H bond functionalization. Currently, methods for C–H bond functionalization rely on precious metal catalysts that present environmental and health concerns. Earth abundant metals have been explored as sustainable catalysts; however, these systems are difficult to develop because of their distinct chemical properties and reactivity patterns compared to 4d and 5d metals. Several reported monometallic iron imido MLMB species capable of nitrene group transfer do so by accessing high-spin states, although their instability limits their applications. Bimetallic species were proposed to improve stability, but these complexes are difficult to synthesize and appeared to be unreactive. Herein, we disclose the Lewis base enhanced C–H bond functionalization mediated by a diiron alkoxide species. Alkoxide ligands were employed to synthesize high-spin bimetallic species due to their weak field and π-donor character, and substituted pyridines were utilized as a handle for nuclearity and reactivity control. Sterically encumbered pyridines allowed access to asymmetric bimetallic complexes (2.5a and 2.6a) and electron rich pyridines resulted in the monometallic analogs (2.2a-2.4a). Electron withdrawing p-trifluoromethylpyridine selectively accessed both the asymmetric dinuclear and mononuclear species indicative of electronic and steric controls. Diiron imido species were isolated with and without pyridine via nitrene capture with aryl azides (3.2a, 3.2b, 3.6a, and 3.6b) and demonstrated Lewis based enhanced toluene amination through a bimetallic pathway. In chapter 5, we will discuss the phosphine-catalyzed regio- and stereoselective hydrophosphination of 1,3-diynes. Diynes are important scaffolds for synthesizing π-conjugated organic frameworks for applications in organic synthesis and materials. The selective functionalization of diynes allows researchers to control the chemical properties of highly conjugated compounds for applications in optic and data storage devices. Phosphines have been shown to enhance the photochemical properties of unsaturated frameworks because of their unique metal-like properties; however, the hydrophosphination of 1,3-diynes is scarcely reported and requires the use of precious metals, alkali metals, or prefunctionalized materials. In this dissertation, we describe a facile method to access previously unreported (E)-(1,4-diphenylbut-1-en-3-yn-2-yl)diphenylphosphanes via the organocatalytic hydrophosphination of 1,4-diphenylbuta-1,3-diynes. The reaction employs catalytic n-tributylphosphine, has a mild substrate scope, and proceeds in a regio- and stereoselective fashion. In chapter 4, we will discuss the development of small molecule anti-invasion agents for the treatment of metastatic cancer. Metastasis remains the leading cause of anti-cancer treatment therapy and cancer-related death. The rapid spread and mutation of the cancerous cells complicates treatment and increases the chance of recurrence. Treatment options are limited because most anti-cancer agents inhibit tumor growth or cause apoptosis, but do not inhibit cancer spread, which is imperative for treating metastatic cancer. Recently, small molecule PDZ1i displayed anti-invasion activity and showed improved survival in multiple in vivo metastatic cancer mouse models. Inspired by PDZ1i, we conducted a structure activity relationship study of related small molecules with the aim of improving anti-invasion activity. Herein, we report a focused library of substituted 1-(benzo[d]thiazol-2-yl)-3-phenylurea derivatives inspired by the anti-invasion and anti-metastatic agent, PDZ1i. Our studies revealed that 1-(benzo[d]thiazol-2-yl)-3-phenylurea derivatives bearing 6-trifluoromethyl (4.3y) and 6-bromo (4.3aa) substituents display anti-invasion activity comparable to PDZ1i. The reported 1-(benzo[d]thiazol-2-yl)-3-phenylurea derivatives serve as promising starting points for future investigations of small molecule anti-invasion agents with potential to prevent and treat metastatic cancers.
- Practical Pathways to Efficient MRAM: Spin-Orbit Torques, Low-Damping, and Anomalous Hall Conductivity in Polycrystalline MaterialsMaizel, Rachel Emily (Virginia Tech, 2026-02-26)There are multiple pathways forward to next generation magnetic random access memory. In this thesis we explore two simple solutions with industry implementation in mind. The first is a low-damping (α< 5×10⁻³) ferromagnetic single-layer with modest anti-damping spin-orbit torque (SOT), $θ_{DL} ≈ 0.05. Here, we investigate an alternative approach to the traditional heavy metal/ferromagnet bilayer to produce SOTs, which suffers from high-damping that is detrimental to energy-efficiency. Instead, of breaking inversion symmetry at the interface we continually break symmetry along the thickness axis by creating an intentional compositional gradient that is purely ferromagnetic and maintains low damping. Crucially, we find that a compositional gradient is not necessary to achieve large damping-like SOTs, instead finding direct evidence from grazing-incidence x-ray diffraction for a strain gradient. The next pathway investigated is an easy-to-grow, polycrystalline alternative to non-collinear antiferromagnets which require high temperature growth (>400°C). We find that sputter-grown γ-FeMn with no post-annealing, has a small non-zero net magnetization (≈(0.02-0.07)μB/atom) and perpendicular magnetic anisotropy only slightly larger than those found in non-collinear antiferromagnets like Mn₃Sn while still exhibiting a large anomalous Hall conductivity of 14 S/cm at room temperature. We show that these unique magnetic and transport properties are the result of pinning at the grain boundaries which can be tuned to enhance the anomalous Hall conductivity.
- Scalable Surrogates for Counts and Computer ExperimentsBarnett, Steven D. (Virginia Tech, 2026-02-26)Data collected by the Interstellar Boundary Explorer (IBEX), recording counts of heliospheric energetic neutral atoms (ENAs), exhibit a phenomenon that has caused space scientists to revise hypotheses about the physical processes, and computer simulations under those models, that are in play at the boundary of our solar system. Providing estimates and associated uncertainty quantification (UQ) of the rate at which ENAs are generated is vital to theory development and validation. Gaussian processes (GPs) constitute an excellent nonparametric regression tool that can provide accurate out-of-sample prediction and UQ. But GPs are unconventional for modeling non-Gaussian observations, are inefficient on large training data, and struggle to model nonstationary response surfaces, all issues present in the IBEX application. To address this gap, I propose a fully Bayesian, Vecchia-approximated, Poisson deep GP surrogate model. I demonstrate its improved predictive capability over competitors through multiple simulated examples. Further, I develop a novel, fully Bayesian framework for solving Bayesian inverse problems, coupling a Poisson response with a Vecchia-approximated GP surrogate of an expensive simulator with high-dimensional output. I demonstrate the utility of this new framework via simulated scenarios in terms of recovering the "true" computer model parameters and enhancing prediction over models that rely exclusively on physical observations. I apply these new technologies to IBEX satellite data and associated computer models developed at Los Alamos National Laboratory.
- Assessing the Effects of Exoskeletons on Physical Demands, Trip and Slip Risks, and User Perceptions in Manual Mining TasksAkinwande, Feyisayo Alexander (Virginia Tech, 2026-02-25)Work-related musculoskeletal disorders (WMSDs) are a major health concern worldwide in the mining sector and are associated with frequent exposure to risk factors prevalent in manual mining tasks. Occupational exoskeletons (EXOs) are a promising ergonomic intervention to mitigate WMSD risk, by reducing physical demands and improving work performance. The purpose of this dissertation was to assess the potential benefits of using EXOs for addressing health and safety challenges encountered by miners, while also examining the limitations associated with EXO use, as a means of providing new evidence to guide the effective selection and application of passive arm-support exoskeletons (ASEs) and back-support exoskeletons (BSEs), help avoid unintended/preventable side effects resulting from this technology, and aid in maximizing the benefits of EXO use in mining. The first study identified and assessed the opportunities for and feasibility of implementing EXOs in mining, through an online survey with industry stakeholders. Miners reported potential benefits of EXOs for lifting and overhead work and shared concerns about EXO use. They also emphasize the need to ensure task compatibility, comfort, and affordability to ensure safe and effective adoption in mining. The second study quantified the potential benefits and risks of using ASEs and BSEs for diverse manual mining tasks using controlled lab-based simulations. Both ASE and BSE effects were device- and task-specific. BSEs significantly reduced peak trunk extensor activity during lifting and overhead installation tasks, although perceptions of exertion and discomfort differed by device: soft BSE reduced perceived upper-back exertion, whereas rigid BSE increased waist/hip discomfort. ASEs also differed in their effects on total shoulder muscle activity across tasks, but their use reduced perceived exertion across most body regions with minimal reported discomfort. The third study assessed the effects of BSEs on trip and slip risks during load carriage on different surface slopes. Using both BSEs differentially altered minimum foot clearance (MFC) and required coefficient of friction (RCoF). Rigid BSEs increased right foot MFC and RCoF, whereas the soft BSE largely preserved baseline gait mechanics, with no significant effects on objective slip or trip risk metrics. Overall, we found that the efficacy of ASEs and BSEs are highly device- and task-dependent. These results provide critical insights to inform evidence-based guidelines for the safe implementation of occupational EXOs in mining and other physically demanding industries.
- Overcoming Challenges in Reversible Addition–Fragmentation Chain Transfer Polymerization using Photoinduced Electron/Energy Transfer CatalysisBaker, Jared Galen (Virginia Tech, 2026-02-24)The development of polymerization methodologies is discussed, with an emphasis on addressing two limitations in reversible addition–fragmentation chain transfer (RAFT) polymerization. Both methods employ photoinduced electron/energy transfer (PET) catalysis to generate radicals within the polymerization system. PET catalysis was selected as the initiation pathway because the rate of radical introduction is tunable across a wide range of conditions, including, but not limited to, photocatalyst identity, photocatalyst concentration, wavelength of light, light intensity, and temperature. The first limitation that is discussed is the incorporation of a single monomer unit at a defined position within the backbone of a polymer chain. Previously, a single monomer unit could be incorporated only at the beginning or end of a polymer chain in reversible-deactivation radical polymerization (RDRP), or otherwise, single units could undergo multiple incorporations. Using expansive condition screening with PET-RAFT polymerization, a set of conditions was identified that resulted in a single-unit monomer insertion (SUMI) within the polymer backbone. The reaction depended on polymer concentration, monomer concentration, and temperature, and resulted in no detectable double- or higher-order insertions. The second limitation addressed was the blocking order requirements associated with both RAFT polymerization and RDRP. This limitation had previously been studied in the field, but it either exhibited termination reactions or applied only to specific systems. Using in-depth kinetic experiments and computational studies, we identified unique conditions that enabled us to overcome the blocking-order requirements associated with RDRP. Polymer and photocatalyst concentrations were crucial to the success of the reaction. Using this method, the impact of blocking order on material properties was evaluated and found to affect material behavior significantly. The method yielded a novel high-molecular-weight thermoplastic elastomer that retained its shape. Expanding on the second method, we sought to maximize chain end fidelity and further elucidate the underlying rates of the technique. By coupling the development of new characterization methods to quantify rates within the system and extensive kinetic experiments, the ratio of the rate of trithiocarbonate activation to the rate of trithiocarbonate termination could be measured. By optimizing conditions to achieve a high ratio of trithiocarbonate activation to termination, a significant increase in chain end fidelity relative to the previously identified conditions was achieved and led to a deeper understanding of which conditions are vital to the method. Lastly, the impact of PET-RAFT polymerization on the uniformity and properties of polymer networks is discussed. In this study, PET-RAFT polymerization yielded controlled networks initially, but could not yield controlled chain extended networks, resulting from decreased chain mobility in the networks. However, PET-RAFT polymerization enabled access to tunable properties, resulting in changes to the hydrophobicity and swelling ratios of the networks.
- Beyond Oil Wealth: Resiliency of the Aliyev Administration in AzerbaijanSullu, Yagiz (Virginia Tech, 2026-02-24)In political science literature, many scholars highlight how natural resources, particularly oil, have often been more of a curse than a blessing for developing countries. The Dutch Disease phenomenon highlights that the rapid development of the natural resource sector leads to a decline in other sectors, primarily the manufacturing and agricultural industries. It also leads to currency appreciation, which makes a country's exports more expensive and less competitive in the global markets. Politically, developing countries with rich natural resources tend to be more authoritarian, and oil wealth contributes to the durability of authoritarian regimes. Many scholars have predicted that oil-dependent regimes would be vulnerable to oil price shocks and periods of declining production. However, examining the political trajectories of oil-dependent regimes during this period reveals that while some have experienced political instability and regime breakdown, others continue to remain in power. The literature on the politics of oil offers some insights into why certain regimes persist while others collapse during oil price shocks. However, the terminal decline in oil production is an emerging concept, and its political impact has received limited attention in the literature. In a case study of Azerbaijan, this dissertation aims to explain the durability of Ilham Aliyev's oil-dependent regime amid a terminal decline in oil production that started in 2010. Drawing on theories of how political institutions contribute to regime durability, this dissertation will highlight the role of the regime's ruling New Azerbaijan Party and its coercive institutions in maintaining power during this challenging time.
- Kinetics of propylene disproportionation over a cobalt oxide-molybdena-alumina catalystLewis, Michael Justin (Virginia Polytechnic Institute, 1968)
- The thermodynamic behavior of polyethylene at its melting pointWaldman, Nathan (Virginia Polytechnic Institute, 1967)
- Structures and incentives in the public provision: a comparative analysis of finances between community college systems of Virginia and North CarolinaClark, Jeff Ray (Virginia Polytechnic Institute and State University, 1974)
- The metabolism of cellulose dextrins by Cellvibrio gilvusVessal, Mahmood Ismail (Virginia Polytechnic Institute, 1967)
- Cyclic loading and crack propagation--an elastoplastic finite element studyCandogan, Ali (Virginia Polytechnic Institute and State University, 1974)