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Sustainable Robotic Construction: A Computational Particle Packing Approach for The Development of Sustainable, Low-cement 3D Printable Materials
No full textConstruction 3D Printing (C3DP) holds great potential for automated construction but faces key challenges, including the high Portland cement content of its printing materials. The high cement content raises material costs, causes shrinkage and thermal cracking, and increases its carbon footprint. This study introduces a novel hybrid computational pipeline that combines image based automated gradation analysis with 2D stochastic particle packing simulation, to design low-cement printable materials with minimal experimental testing. The image-based gradation system achieved a mean absolute error under 3.64% across six fine and coarse aggregate types. The particle packing simulation demonstrated an average error of less than 1.7%, with a maximum error of 2.2% across 225 simulation cases involving 46 aggregate blends. Using the simulation outputs, four printing materials were designed and tested, with cement contents ranging from 355 to 385 kg/m³, achieving a 35-45% reduction in cement compared to conventional printing mixtures. The mixture with the highest packing density and the lowest cement content (355.8 kg/m³) showed the highest 14-day flexural strength of 6.86 MPa, along with acceptable shape stability and printability. The proposed computational framework minimizes the need for extensive, time-consuming trials while enabling significant cement reduction without compromising mechanical performance. It offers a scalable approach to designing printing materials with local aggregates, thereby lowering carbon footprints, minimizing the risk of shrinkage cracking, and improving the economic viability of C3DP
Versatile Nitration of BODIPY Dyes Using NO₂BF₄: Effects of Nitro Substituents on Spectroscopic and Self-Assembly Properties
No full textThis study explores the regioselective nitration of BODIPY dyes at the 2, 3- and 2,6-positions using nitronium tetrafluoroborate (NO₂BF₄), offering a high-yielding and mild synthetic route. The introduction of nitro groups significantly alters the dyes’ photophysical and self-assembly properties. Mono-nitrated BODIPYs exhibit hypsochromic shifts in absorption and emission spectra, increased dipole moments, enhanced Stokes shifts, and reduced molar absorptivity. In contrast, di-nitrated analogs show bathochromic shifts and decreased dipole moments in both ground and excited states. Spectroscopic characterization was performed using UV-vis and fluorescence spectroscopy, supported by density functional theory (DFT) calculations. Self-assembly behavior was investigated in polar (acetonitrile) and non-polar (toluene) solvents, revealing solvent-dependent fluorescence quantum yields and aggregation tendencies. Atomic force microscopy (AFM) confirmed aggregation in aqueous media and its absence in organic solvents. These findings demonstrate the tunability of BODIPY dyes through nitration and highlight their potential application as polarity-sensitive probes in diverse environments
ENABLING ASSEMBLY AND REPAIR OF DISSIMILAR THERMOPLASTIC COMPOSITES FOR SPACE APPLICATIONS VIA ULTRASONIC WELDING
No full textInterest in the repair and reuse of thermoplastic composites (TPCs) is growing, especially for lightweight space/lunar structures. Ultrasonic welding (USW) is a promising joining technique by which vibration is applied to create heat. An energy director (ED) is used at the joint interface to concentrate heat generation to the desired surface. This work explores the effect of dissimilar ED materials on the disassembly repair of TPCs using USW, to potentially tailor weld properties for specific applications. Single lap joints were created using carbon fiber (CF)/polyether ether ketone (PEEK) adherends with PEEK, polyphenylene sulfide (PPS), polyetherimide (PEI), and low melt polyaryletherketone (LM-PAEK) as EDs. Differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA), and degree of healing tests were performed on all ED materials. PPS showed the least compatibility due to the large difference between its melting temperature (281.9°C) and the PEEK TPC matrix (345.0°C). Regular welds used PEEK and PEI EDs welded at 1000 N and PEI and PPS EDs welded at 500 N; these samples all initially had 40% travel (the sonotrode moved 40% of the ED’s thickness downwards). Low travel welds used PEEK, PEI, and LM-PAEK EDs welded with 20% travel and 750-800 N of welding force. Regardless of the initial weld parameters, significant interlaminar fracture occurred upon disassembly. PEEK (1000 N) and PEI (1000 N) had comparable LSSs (29.4 MPa and 30.1 MPa) to the low travel PEEK and PEI samples (31.3 MPa and 28.0 MPa). Samples were rewelded for two repair cycles, but LSS recovery was low due to the poor joint surface contact from the damaged interfaces. LSS recovery typically varied between 25% and 50% for both repairs. However, low travel welds were only repaired once because the 20% travel could not overcome the damage incurred after the first repair. The LM-PAEK samples could not be repaired at all, likely due to reduced material compatibility
Exploring Runtime Evolution In Android: A Cross-Version Analysis And Its Implications For Memory Forensics.
No full textUserland memory forensics has become a critical component of smartphone investigations and incident response, enabling the recovery of volatile evidence such as deleted messages from end-to-end encrypted apps and cryptocurrency transactions. However, these forensics tools, particularly on Android, face significant challenges in adapting to different versions and maintaining reliability over time due to the constant evolution of low-level structures critical for evidence recovery and reconstruction. Structural changes, ranging from simple offset modifications to complete architectural redesigns, pose substantial maintenance and adaptability issues for forensic tools that rely on precise structure interpretation. Thus, this paper presents the first systematic study of Android Runtime (ART) structural evolution and its implications for memory forensics. We conduct an empirical analysis of critical Android runtime structures, examining their evolution across six versions for four different architectures. Our findings reveal that over 73.2% of structure members underwent positional changes, significantly affecting the adaptability and reliability of memory forensic tools. Further analysis of core components such as Runtime, Thread, and Heap structures highlights distinct evolution patterns and their impact on critical forensic operations, including thread state enumeration, memory mapping, and object reconstruction. These results demonstrate that traditional approaches relying on static structure definitions and symbol-based methods, while historically reliable, are increasingly unsustainable on their own. We recommend that memory forensic tools in general and Android in particular evolve toward hybrid approaches that retain the validation strength of symbolic methods while integrating automated structure inference, version-aware parsing, and redundant analysis strategies. These adaptations are essential for sustaining effective and trustworthy forensic capabilities amidst rapidly evolving runtime environments
INTERSECTIONALITY AND GEOGRAPHICAL DIVERSITY IN DIALOGUE WITH WORKS BY MARYSE CONDÉ, ANANDA DEVI AND DJAILI AMADOU AMAL
No full textThis thesis examines how intersecting systems of oppression, including gender, race, class, culture, and colonial legacy, shape women’s experiences of marginalization and resistance in Francophone literature. Through a comparative analysis of Maryse Condé’s Victoire: Les saveurs et les mots, Ananda Devi’s Ève de ses décombres, and Djaili Amadou Amal’s Les Impatientes, the study explores how geography and historical context influence both the manifestation of marginalization and the fragility of female agency. In comparing these texts, which are set in three distinct Francophone regions, namely Guadeloupe, Mauritius, and Cameroon, the research highlights how location plays a crucial role in shaping the specific forms of marginalization and resistance depicted in each narrative. Bringing Kimberlé Crenshaw’s framework of intersectionality into dialogue with feminist, postcolonial, and decolonial thought as well as the literary texts themselves, the research argues that intersectionality provides the foundational lens through which overlapping structures of domination become visible, and that this foundation allows the analysis to identify additional dimensions of identity shaped by colonial, postcolonial, and transnational contexts that extend beyond its original formulation. The analysis demonstrates that women in these novels are not only constrained by gender, race, and class but also by geographical and cultural conditions rooted in colonial histories. Consequently, this thesis proposes a multidimensional framework attentive to geography, culture, and colonial histories and legacies; one that offers a more comprehensive understanding of female marginalization and resistance across Francophone geographies, while underscoring that women’s resistance alone is insufficient unless the violent and oppressive structures themselves are dismantled
Management of Herbicide-Resistant Italian Ryegrass Using Cover Crop and Fall Residual Herbicide
No full textA field study was initiated in the fall of 2023 and repeated in 2024 at the LSU AgCenter Northeast Research Station near St. Joeseph, LA, to determine the impact of fall-applied soil residual herbicide at different growth stages (spike and one-leaf stage) on grass cover crop species, cereal rye and black oats. In most instances, clomazone (631 g ai ha-1) and treatments containing the higher rates of metribuzin (263 g ai ha-1)resulted in the greatest amount of cover crop injury both years, with biomass impacted by clomazone both years and in one of two years with the treatments containing the higher rate of metribuzin. A more pronounced cover crop visual injury was observed with S-metolachlor (1,421 g ai ha-1), metribuzin (146 g ai ha-1) containing treatments, and pyroxasulfone plus fluthiacet-methyl (141 g ai ha-1) in 2024 vs. 2023. This was attributed to 2.7-times increased rainfall received within 14 DAT of fall-applied residual herbicides in 2024 resulting in waterlogged soil and potentially reducing plants’ ability to metabolize those herbicides. Injury was more pronounced at the spike stage application timing, but the difference was not evident in cover crop biomass reduction. In 2024, cover crop biomass was only negatively impacted with clomazone applied to black oats while in 2025 biomass was reduced following the application of clomazone and treatments containing the higher rate of metribuzin, regardless of the cover crop species. Also, in 2025, cereal rye was more sensitive to fall-applied herbicides at the spike stage while black oats were more sensitive at the later timing.
A separate field study was initiated in the fall of 2023 and repeated in 2024 at the LSU AgCenter Northeast Research Station near St. Joeseph, LA to determine the impact of fall-applied herbicide of S-metolachlor at 1421 g ai ha-1 or no fall-applied herbicide, cover crop of cereal rye or no cereal rye, and termination timing on Italian ryegrass control with glufosinate or paraquat applied 4 or 2 weeks before planting or at planting. Italian ryegrass control was maximized with the combination of cereal rye cover crop and S-metolachlor applied at the spike stage of the cover crop in the fall. Cereal rye alone controlled Italian ryegrass 70 to 73% 8 to 12 WAP while S-metolachlor alone resulted in 76 to 84% control. The combination resulted in 97 to 99% 8 to 12 WAP. In addition, Italian ryegrass tiller count, reproductive tillers, and biomass reduction were greatest with the cereal rye and S-metolachlor combination in 2024. In 2025, only the addition of cereal rye cover crop to S-metolachlor had a positive impact on those parameters
DEVELOPMENT AND APPLICATION OF PHBV / BIOMASS COMPOSITE PELLETS FOR COST EFFICIENT DENITRIFICATION SYSTEM
No full textAbstract
The viability of bioplastics as denitrification substrate is well established in literature. However, their high cost has limited the practical integration of bioplastic-based systems into wastewater treatment plants. This study investigates the preparation and evaluation of composite pellets comprised of Poly(3-hydroxybutyrate-co-3-valerate) (PHBV) and plant biomass. Four renewable agricultural wastes, namely sugarcane bagasse, sawdust, rice husk, and switchgrass were incorporated as the biomass component and were blended with PHBV to reduce overall material costs.
Composite pellet formulations were prepared with varying biomass-to-PHBV ratios (50-90% biomass) using a heated pelletizer and hydraulic press. Pellet cohesiveness was initially assessed through 30 days of water submersion test. Chemical oxygen demand (COD) releases were also monitored for 11 days, revealing that all sugarcane bagasse-PHBV ratios released carbon gradually over time when compared to other blends. Mechanical testing indicated that sugarcane bagasse-PHBV composites achieved the highest compressive strengths among all the biomass-PHBV blends across all tested ratios. The 50:50 bagasse-PHBV showed the maximum axial compressive stress (143.10 ±7.25 MPa) and largest axial compressive strain (0.273± 0.059 mm/mm) of all compositions evaluated. Analyses of stress-strain testing further validated the structural integrity of these composite pellets. However, two-way ANOVA revealed that biomass type significantly (p values \u3c 0.05) affected both compressive stress and strain, whereas the biomass-PHBV ratio influenced only strain significantly (p \u3c 0.05). Among the pellets that passed the water cohesiveness test and exhibited low-COD releasing tendency, biomass type and blending ratios were selected to maximize compressive strength while minimizing PHBV content. After mechanical testing, sugarcane bagasse emerged as the most suitable biomass and was selected for all laboratory-scale denitrification experiments. Three sugarcane bagasse-PHBV ratios (70:30, 80:20, and 90:10) were compared with pure PHBV controls to compare nitrate removal and pellet degradation rates in a triplicate, closed-looped recirculating systems.
Nitrate conversion rates varied between 1.5 and 2.9 kg NO3--N/m3·day across all blends. All blend ratios performance values were closely similar and comparable to control, indicating no difference in denitrification performance. Statistical analysis (one-way ANOVA, p=0.212; Dunnett’s p \u3e 0.05) also confirmed that nitrate removal rates did not vary significantly among the PHBV control and bagasse/PHBV ratios at the 95% confidence level. Although all sugarcane bagasse-PHBV composite pellets effectively supported denitrification, the 90:10 formulation exhibited significant disintegration after day nine, limiting its long-term stability and applicability as a denitrification media.
These findings on short-term denitrification experiments highlighted that the selection of the bagasse-PHBV blend ratio should be based on stability and cost efficiency. The 90:10 blend ratio degraded rapidly, while 70:30 blend maintained long term stability. Economic analysis showed that 80:20 bagasse-PHBV achieved most cost-effective performance, reducing substrate cost by 74% per ton of NO3--N removed. This study demonstrates a potential scalable pathway for reusing underutilized agricultural waste into eco-friendly products that deliver both environmental and economic benefits. However, it has to be noted that pellet performance in longer term denitrification experiments (60-90 days or longer) has to be assessed for selecting the ideal blending ratio.
Keywords: PHBV, biodegradable pellets, renewable biomass, denitrification, aquaculture, sustainable materials, packaging, solid carbon source
Modeling Shape Memory Polymers: From Thermodynamic Principles to Physics-Informed Data-Driven Machine Learning
No full textShape memory polymers (SMPs) are a class of stimuli-responsive materials capable of recovering large deformations when exposed to external triggers such as temperature changes. Their distinctive thermomechanical behavior, including the shape memory effect, nonlinear viscoelasticity, and time-dependent softening under cyclic loading, requires a robust and comprehensive constitutive framework. Traditional modeling approaches often struggle to accurately capture the coupled nonlinear, temperature-dependent, and damage-driven features observed in SMPs at large strains. After a brief review of SMP applications in Chapter 1, Chapter 2 focuses on developing a finite-deformation constitutive model rooted in rational thermodynamics. The formulation integrates nonlinear hyperelasticity, viscous dissipation through a multi-branch Maxwell network with nonlinear viscosity, and stress-softening (Mullins effect) using internal state variables. The model is calibrated and validated through extensive experimental testing across various temperatures and strain rates, demonstrating its ability to reproduce complex SMP behavior with high fidelity and computational efficiency. Although physics-based models provide interpretability and adherence to thermodynamic principles, their complexity and calibration demands often become prohibitive in multi-physics environments or large datasets. To address these limitations, Chapter 3 introduces a hybrid physics-informed machine learning (PIML) framework. This approach combines Gaussian Process Regression (GPR) for modeling equilibrium hyperelastic behavior with Recurrent Neural Networks (RNNs) for capturing history-dependent, nonlinear viscoelastic responses. Physical constraints—including objectivity, symmetry, and the Clausius–Duhem inequality—are embedded into the architecture to ensure thermodynamic consistency. The resulting surrogate model captures multiaxial, rate-dependent behavior with robustness against data sparsity and noise, offering a generalizable and physically constrained predictive tool for advanced soft-material simulations. Chapter 4 further advances this direction by developing a physics-informed Temporal Convolutional Network (TCN) capable of learning nonlinear thermo-viscoelastic behavior with Mullins-type damage. The model enforces thermodynamic consistency while delivering accurate cyclic predictions under large deformations. Finally, Chapter 5 presents a Hencky-strain-based, Holzapfel-type constitutive framework for both solid and foam SMPs. Implemented in Abaqus/Explicit and validated against experimental data and numerical benchmarks, this model effectively predicts highly nonlinear thermomechanical responses across diverse loading and thermal conditions
Beyond Nostalgia: Reinventing Home Within the Ruins of Exile in Arab Women’s Memoirs
No full textThis dissertation argues that contemporary exiled Arab American women memoirists—Leila Ahmed, Etel Adnan, and Mona Hajjar Halaby—turn life writing into a decolonial instrument, wielding the memoir as both refuge and rebellion. It contends that exile and nostalgia, often perceived as sites of loss, offer instead a generative vantage point from which to reconstruct selfhood. Moving beyond nostalgia as a paralyzing sentiment, this project critically interrogates nostalgia through a postcolonial and gendered lens—an insurgent practice that repurposes memory to dismantle imperial and patriarchal scripts.
Through the close reading of three memoirs, the dissertation traces a trajectory of decolonial strategies. The first chapter examines Etel Adnan’s work as a poetics of metaphysical exile, where she inhabits a realm similar to Lacanian Imaginary to unbind herself from colonial constructs of home and language. The second chapter analyzes Leila Ahmed’s A Border Passage as an enactment of disruptive nostalgia—a method of excavating and reassembling cultural fragments to author a self beyond the colonial script of Arabness. The final chapter turns to Mona Hajjar Halaby, for whom return is not an endpoint but an ongoing intergenerational practice of (re)construction; sustained through the gendered diasporic labor of transforming her mother’s letters into a public counter-archive.
Integrating frameworks from Edward Said, Franz Fanon, and other critical scholars, this project reveals the memoir as a critical technology of selfhood. These memoirists appropriate language itself—through catachresis, multilingualism, and archival curation—to refuse colonial interpellation and assert a right to self-narration. In doing so, they expose the memoir as both sanctuary and weapon: a site where exile’s fractures become fertile ground for creative reconstruction. Overall, this dissertation proposes a new taxonomy of resistance, positioning these works not merely as personal testimonies, but as decolonial blueprints that transform displacement into a continuous, generative act of (re)construction
Environmental heterogeneity across an urban gradient influences detritus and nutrients within artificial containers and their associated vector Aedes sp. larvae in San Juan, Puerto Rico
No full textDetrital inputs from the surrounding terrestrial environment provide essential nutrients that sustain mosquito populations in aquatic containers. The larvae of Aedes aegypti (L.), an anthropophilic invasive vector species, often develop in artificial habitats in urban areas but little is known about how that environment shapes their life history or phenotypic traits. We hypothesized that container detritus, nutrients, and larval interspecific competition with the endemic mosquito, Aedes mediovittatus (Coquillett), would vary along an urban gradient in the San Juan Metropolitan Area in Puerto Rico. We also hypothesized that fine-scale variations within a 200 m buffer of the container environment would alter Ae. aegypti larval nutrients, density, and biomass. We sampled mosquito larvae, container detritus, and suspended particulate organic matter in 44 locations and characterized the surrounding environment in terms of land cover, land use, and vegetation α diversity. We show that container detritus and nutrients are influenced by fine-scale environmental variations environment, affecting Ae. aegypti and Ae. mediovittatus larvae phenotypic traits and nutrient composition. Aedes aegypti was the dominant species in all samples across the urban gradient. We found a negative relationship between Ae. mediovittatus larval % carbon and vegetation cover in the surrounding environment, and a negative correlation between this species\u27 larval C:N and suspended particulate organic matter C:N. These findings suggest a potential disadvantage in nutrient allocation that could affect its competitive ability in urban areas. We found smaller and less nitrogen enriched (δ¹N) Ae. aegypti in containers surrounded by higher impervious cover. The implications of these findings on potential vector disease risk across urban gradients are discussed