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Recent Submissions
Designing Metal/Zeolite Catalysts for Methane Dehydroaromatization: Decoupling External Site Effects, Bimetallic Interactions, and Deactivation Pathways
Hossain, Md Sifat (Virginia Tech, 2026-05-20)
Methane, the primary component of natural gas, is an abundant yet underutilized carbon resource that is frequently flared or vented, contributing to greenhouse gas emissions and energy loss. Methane dehydroaromatization (MDA) provides a direct, COx-free route to convert methane into benzene and hydrogen, offering a promising pathway for methane valorization. Mo/ZSM-5 is the most extensively studied catalyst for this reaction, yet its practical application is constrained by rapid deactivation caused by carbon deposition and low product yield. In Mo/ZSM-5 catalysts, the catalytically relevant active phase is widely attributed to Mo carbide or oxycarbide species confined within the zeolite channels. Alongside these desired intrachannel active sites, a fraction of Brønsted acid sites (BAS) and MoOx species can reside on the external surface of the zeolite. These external sites are known to promote unselective reactions, including oligomerization of intermediates and excessive carbon deposition, which accelerate catalyst deactivation. The individual roles of external BAS and external MoOx species remain difficult to distinguish experimentally. In parallel, the incorporation of promoters such as Fe, Ni, or Co into Mo/ZSM-5 has been reported to improve catalytic stability and product selectivity; however, the fundamental origin of these improvements remains unclear, particularly with respect to whether true bimetallic interactions form within the zeolite channels and how they influence active site formation and carbon deposition pathways. This dissertation addresses these challenges by systematically investigating how external site engineering and bimetallic interactions in Mo- and Mo-Fe/ZSM-5 catalysts govern active site formation, catalytic performance, and deactivation pathways, providing a foundation for the rational design of stable MDA catalysts.
A key contribution of this work, addressing the unresolved role of external sites, is the decoupling of the individual roles of external metal oxide species and external Brønsted acid sites (BAS). Using selective silylation of ZSM-5 prior to Mo loading and selective extraction of external MoOx, catalysts were synthesized with controlled distributions of metal and acid sites. Catalytic testing, including tandem-bed experiments, revealed that external BAS, while do not activate methane, strongly promote oligomerization of reaction intermediates and products, resulting in decreased benzene selectivity and accelerated formation of hard, graphitic coke. In contrast, external MoOx formed smaller amounts of softer, more disordered carbon and played a comparatively minor role in deactivation. These findings provide a mechanistic basis for targeted external site passivation strategies in Mo/ZSM-5 catalysts.
Building on the understanding of external site effects, this dissertation also examines how precursor chemistry influences metal distribution and catalytic performance by introducing Fe2(MoO4)3/ZSM-5 as a bimetallic precursor. Compared with monometallic MoO3/ZSM-5 and mixed MoO3+Fe2O3/ZSM-5 containing equivalent metal loadings, Fe2(MoO4)3/ZSM-5 exhibited superior benzene selectivity and improved catalytic stability. Structural characterization revealed partial segregation of Fe2(MoO4)3 into Fe2O3 and amorphous MoOx during pretreatment, promoting MoOx migration into the zeolite channels while minimizing Mo trapping by external FeOx phases, as observed in MoO3+Fe2O3/ZSM-5 catalysts. Analysis of spent catalysts showed that Fe promotes the formation of carbon nanofibers, contributing to improved catalyst stability. These findings underscore the impact of Mo–Fe interactions originating from the precursor and highlight the importance of understanding Mo–Fe interactions within the zeolite channels.
Building on these insights, direct co-impregnation of Mo and Fe into ZSM-5 was employed to promote co-location of both metals within the zeolite channels and to investigate whether true bimetallic active sites can form under MDA conditions. Advanced spectroscopic characterization and DFT modeling collectively confirmed the presence of distinct MoFeOx species anchored within the zeolite channels in fresh catalysts. Upon activation, these bimetallic domains likely evolve into a unique active site, leading to a markedly higher benzene formation rate and lower deactivation rates compared to monometallic Mo/ZSM-5. The enhanced performance is attributed to Mo–Fe synergy, which influences both methane activation pathways and carbon deposition behavior.
Together, these studies provide a comprehensive understanding of how external site passivation and bimetallic site formation govern activity, selectivity, and deactivation in Mo- and Mo-Fe/ZSM-5 catalysts. This dissertation offers new design principles for engineering stable, high-performance catalysts for direct methane conversion.
High School Dropout Among Black Male Students: Lived Experiences of Institutional Disconnection and Academic Resilience
Spruill, Tonya Lenee (Virginia Tech, 2026-05-20)
The attrition and dropout of Black male students in high school continued to highlight persistent and critical inequities within the educational system. Despite decades of reform efforts, Black male students continued to experience disproportionately higher rates of academic disengagement, contributing to outcomes of high school dropout. The purpose of this qualitative study was to examine the lived experiences of former Black male students, aged 18–22, who dropped out of high school prior to their cohort year, and the multifaceted factors that contributed to this phenomenon through the lens of critical race theory. Data collection methods included semi-structured interviews with three high school dropouts who provided insight into cultural disconnection, limited access to academic and social support systems, punitive disciplinary approaches, and the lack of mentorship that shaped their engagement with schooling and academic persistence. Using critical race theory (CRT), this study provided a framework for examining how racism, disciplinary inequities, and deficit-based perceptions contributed to the attrition and dropout of Black male students. Thematic analysis was used to systematically identify, organize, and interpret patterns of meaning within the qualitative data collected from the interviews, connecting the lived experiences of Black male students to the systemic factors that influenced attrition and dropout. The findings will assist school districts, policymakers, and educators in informing interventions to reduce attrition and dropout rates, identifying effective programs for potential replication, and offering recommendations to stakeholders to improve graduation rates among Black male students. Overall, the study aimed to provide actionable recommendations for educators, administrators, and policymakers committed to reducing dropout rates and fostering inclusive, supportive, and high-achieving school environments for Black male students.
Approximation and Feedback Control of Nonlinear Systems with Applications to Thermo-Fluids
Bouland, Ali A. M. A. A. (Virginia Tech, 2026-05-20)
This dissertation studies approximation and feedback control for nonlinear systems, with an emphasis on high-dimensional thermo-fluid models arising from fluid dynamics and indoor-air applications. The central challenge is that many nonlinear control problems originate from partial differential equations whose discretizations are too large for direct optimization, analysis, or real-time feedback design. This work shows that such problems can be made tractable by utilizing approximation theory, model reduction, and nonlinear feedback synthesis. The first part of the dissertation develops theoretical results for offline value-function approximation in reproducing kernel Hilbert spaces. In a class of native spaces, explicit rates of convergence are derived for approximations generated within a policy-iteration framework. These results show that approximation accuracy depends not only on smoothness properties of the basis, but also on the geometric distribution of the centers defining the approximation space, thereby providing a rigorous connection between approximation theory and reinforcement learning-based control. The second part applies control-oriented model reduction and nonlinear feedback design to the fluidic pinball, a benchmark flow-control problem. Using interpolatory model order reduction, the full-order model is reduced from approximately 30,000 states to a reduced model of dimension r=80. A Quadratic--Quadratic Regulator (QQR) is then constructed and evaluated on the full-order model. For Re_D=30, the nonlinear controller achieves the target performance criteria faster than the corresponding linear controller, and for Re_D=50, it stabilizes the flow while the linear controller fails. The final part develops a reduced-order nonlinear control framework for buoyancy-driven indoor-air flows motivated by HVAC applications. A finite-element discretization of the Boussinesq equations produces a large-scale descriptor system with on the order of 5×10^4 degrees of freedom. After linearization, the system is reduced using the Iterative Rational Krylov Algorithm (IRKA) to a control-oriented model of dimension r=26. The reduced model is then used to construct nonlinear feedback through the QQR framework. Closed-loop simulations show improved transient regulation and a reduction in cumulative control cost relative to linear quadratic regulation. Taken together, these results demonstrate that mathematically grounded approximation and model order reduction can bridge the gap between high-fidelity nonlinear models and implementable feedback controllers. The dissertation contributes both new theory for approximation in nonlinear control and new computational methodologies for reduced-order feedback design in thermo-fluid systems.
Optimization of a UAV for Wildfire Management
Hargan, Nathaniel Steele (Virginia Tech, 2026-05-20)
Wildfires pose a significant environmental risk, cause substantial economic damage, and are a danger to human life. Uncrewed aerial vehicles (UAVs) have the potential to support hotshot crews to combat wildfires more effectively. UAVs are valuable due to their low cost and high maneuverability. UAVs with the ability to carry large payloads can effectively transport fire retardant or propellant to create controlled burns remotely, mitigating the risk of uncontrolled wildfires. A UAV designed for this application should be able to carry a large payload, have enough battery capacity to remain in flight for the extent of a mission, and be rigid enough to resist vibration. The UAV must be large enough for the propellers and electrical components needed to lift the payload. The goal of this project is to design a conceptual model of an octocopter UAV and to examine the design space to find an optimal solution. The UAV has a 2-meter wheelbase and is designed to carry a 45kg payload. The UAV model is an 1/8-symmetric sector model of the full UAV, represented as a finite element model, and is used to estimate the deflection, stress, fatigue life, frequency response, and damage. The UAV is modeled as a 3D Timoshenko beam finite element model. The mass and mass moment of the UAV are minimized using non-linear programming.
Reinforcement Learning Benchmarking for Sustainable Energy Systems: Perturbation Robustness, Safety Constraints, and Multi-Agent Coordination
Koruturk, Mehmet (Virginia Tech, 2026-05-20)
Reinforcement learning (RL) has emerged as a promising approach for sequential decision making in sustainable energy systems, yet the lack of systematic benchmarks hinders principled algorithm comparison and deployment. This thesis presents SustainRL-Bench, a comprehensive benchmarking study that evaluates RL algorithms across three sustainable energy environments—electric vehicle (EV) charging coordination, building HVAC control, and cogeneration plant dispatch—along three experimental axes: perturbation robustness, safety constraints, and multi-agent coordination. Our evaluation spans 116 unique configurations totaling over 310 training runs.
Several findings challenge conventional expectations. Perturbation sensitivity varies by over an order of magnitude across environments: EV Charging PPO degrades less than 11% under state perturbation, while Building policies collapse by over 100% at the same relative scale, and in Cogeneration, on-policy PPO remains far more robust than off-policy methods (<24% degradation across all channels vs. order-of-magnitude losses for SAC). Constrained MDP-based safe RL achieves precise constraint tracking only when the cost signal is sufficiently orthogonal to the reward; partial overlap permits tracking at tight limits, while full alignment renders constraints inactive, and off-policy Lagrangian methods fail entirely across all environments. In multi-agent settings, environment coupling structure rather than agent count determines algorithm feasibility, with the single-agent algorithm ranking reversing in tightly coupled domains. All code and configurations are publicly available.