Rice University Electronic Theses and Dissertations

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Rice University makes its graduate theses and dissertations available online at no cost to end users. These electronic theses and dissertations (ETDs) cover the period from 1918, when the first dissertation was issued to H. E. Bray, through the most recently processed graduating year. Occasionally a thesis or dissertation may be be missing from the repository. If you are unable to find a specific dissertation, please let us know and we will attempt to make it available through the repository, provided that the author has not elected for it to be embargoed.


Visit the web site for Rice University's Office of Graduate and Postdoctoral Studies for more information about Rice graduate student requirements for theses and dissertations.


Recent Submissions

Now showing 1 - 20 of 14022
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    Detectivity vs. Sensitivity: Non-Hermitian Metasurface Sensor
    (2023-10-06) Li, Zhichao; Naik, Gururaj
    Detectivity is the most important performance metric of any sensor. Detectivity is limited by the sensitivity of a sensor when the probe significantly overwhelms the detector noise. But, when the probe is limited in its power budget, as in sensors on mobile platforms, high sensitivity does not guarantee high detectivity. Here, we demonstrate the trade-off between the detectivity and sensitivity of a plasmonic sensor. Plasmonic sensors are popular for their high sensitivity arising from large local field enhancements. However, their Q-factors are bad resulting in low detectivity for limited power-budget situations. This problem can be alleviated by using an array of plasmonic structures forming a quasi bound state-in-the-continuum (BIC). The plasmonic BIC sensors show higher detectivity but smaller sensitivity. We identify the physics behind this trade-off and experimentally demonstrate antimouse-IgG sensing in a gold nano-disk array-based plasmonic BIC sensor. Moreover, we induce a non-Hermitian system to control the Q factor by changing the non-radiative loss with little effect on the near field. Using this non-Hermitian structure we can break the trade-off effect
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    A Flexible Multimodal 3D Single-Molecule Super-Resolution Microscope for Whole Cell Imaging
    (2023-07-20) Nelson, Tyler Evan; Gustavsson, Anna-Karin
    Single-molecule super resolution techniques can be used to resolve subcellular structures in nanoscale detail, but they are sensitive to background signal which is common in fluorescently labeled cells. Most microscopes are limited to standard epi- illumination, which generates high background fluorescence by illuminating the entire sample at once. Specialized illumination schemes like light sheets or Total Internal Reflection Fluorescence (TIRF) are useful to improve the resolution, but the usefulness of these methods can be limited in certain regions of the cell. In this thesis, we demonstrate a flexible, multimodal super resolution imaging system which combines the optical sectioning capacity of a tilted light sheet with the excellent contrast and homogeneous illumination of a flat-field epi- and TIRF setup. This imaging platform also includes a two-channel 4f point spread function (PSF) engineering system combined with long axial range phase masks for 3D imaging. We show that our microscope greatly reduces background fluorescence throughout thick mammalian cells and improves the performance of single-molecule super-resolution imaging in cells in both 2D and 3D and has the potential to image in 3D throughout an entire cell.
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    Network science algorithms for the reliability and resilience of engineered infrastructure networks
    (2023-08-11) Fu, Bowen; Dueñas-Osorio, Leonardo
    Critical infrastructure networks are essential engineered systems for modern society, encompassing power grids, telecommunication networks, transportation systems, and water distribution networks, among others. Despite their crucial role in maintaining community normalcy, critical infrastructure networks face a variety of threats, such as aging, extreme weather, intentional attacks, chronic hazards, and catastrophic disasters. Any damage to critical infrastructure networks may be significantly amplified by their interdependencies and the increasing interactions with users and operators, ultimately leading to serious economic losses and potential loss of life. As enhancing the reliability and resilience of critical infrastructure systems is a priority for governance and society’s wellbeing,, different fields of research and practice are needed to develop ideas, test them, and implement them. Traditionally, efforts to improve the reliability and resilience of engineered infrastructure systems have focused on individual components within the systems, such as retrofitting and hardening of bridges in highway networks or substations in power grids. However, infrastructure systems are interconnected in network form, and decisions for retrofit or hardening should consider the broader network perspective. Furthermore, infrastructure systems are interconnected among each other, forming a network of networks (NoNs) due to the existence of cross-network dependencies. Thus, it is necessary to investigate the reliability and resilience of infrastructure systems from a network-level perspective. Network science is a dynamic field that has developed sophisticated techniques and algorithms to investigate the properties of networks, structures in networks, and processes on networks. However, the development of advanced techniques inspired by network science to complex problems in engineered infrastructure systems is still limited. We leverage significant developments in algorithms and techniques from network science and understanding of infrastructure systems to benefit their reliability and resilience. Currently, exact reliability computation methods and optimization-based methods are among the most effective strategies for reliability and resilience management of infrastructure systems, due to their guarantees on the accuracy or optimality of the solution. However, the computational complexity of these algorithms for reliability and resilience, is usually beyond affordable. The conflict between desirable models and practical limitations calls for a rational framework which allows decision-makers to choose an effective alternative option when the optimal solution is not feasible. We address this tension with Simon’s theory of satisficing. By selecting a solution that is ‘good enough’ rather than optimal, satisficing theory is applied to the reliability and resilience of engineered infrastructure systems, on problems such as reliability estimators with guarantees on interval and confidence, and close-to-optimal solutions for optimization models, among others. Inspired by the satisficing theory, we build upon techniques and algorithms from network science and proposed algorithms on multiple computationally intractable problems related to the reliability and resilience of infrastructure systems. Funding allocation on retrofit of bridges in highway networks are usually heavily impacted by the influence of politics, which is at odds to the optimal solution from engineering perspective. Our proposed socio-technical ranking algorithm based on a framework inspired by the Katz centrality from network science can effectively integrate network topology, bridge vulnerability information and impact of politics, and provide a compromise between optimality and practicality. We also proposed a principled recovery algorithm based on network partitioning and percolation process in networks, to restore damaged infrastructure systems quickly with supply-demand balance, which is similar to solutions from mixed-integer optimization models. In addition, we introduce the dimension of resilience into the network dismantling problem in network science to identify a dismantling solution that not only breaks the network, but also delays its recovery. By developing an adversarial-dismantling-retrofit strategy, we reveal critical information for long-term resilience enhancement of infrastructure systems. Finally, we investigate the functional relationship between different components of a transportation network, by extracting its dynamical backbones from real-time traffic data, which supports congestion mitigation, traffic intervention and transportation network design. Overall, inspired by community reliability and resilience challenges, my research builds upon network science methods to develop novel algorithms that address resource allocation to bridges in transportation networks, resilience-based restoration using distributed percolation process, resilience-informed network dismantling algorithms and adversarial-dismantling-retrofit strategies, along with mechanisms of resilience for infrastructure systems via functional decompositions to support dynamics-based design and operation. All these algorithms are implementable in practice, unlike their parent methods which remain intractable for large infrastructure problems of today. By being integrated to the Interdependent Networked Community Resilience Modeling Environment (IN-CORE) platform developed by the National Institute of Standards and Technology (NIST), our proposed algorithms will be implemented to support community resilience. Furthermore, as network science is also at the intersection of physical systems and their information processing capabilities, rendering insights from this research useful for emerging developments in system automation, decentralized consensus, and the development of quantum algorithms implementable in noisy-intermediate scale quantum devices.
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    Understanding the Conditions for Detecting a Phonology to Articulation Cascade in Speech Production
    (2023-08-11) Irons, Sarah T; Fischer-Baum, Simon; Martin, Randi; Niedzielski, Nancy
    Phonetic distortions, subtle acoustic traces of how a competitor would be produced on the articulation of a response, have been used as evidence for cascading activation from phonological planning to articulatory implementation, that is that information flows between these levels of representation in the language production system prior to selection at the phonological planning level. Phonetic distortions are a robust finding, when focusing on speech errors, produced either in tongue twisters (Baese-Berk & Goldrick, 2009; Frisch & Wright, 2002; Goldrick, 2016; Goldrick & Blumstein, 2006; Goldrick et al., 2016; Goldstein et al., 2007; McMillan & Corley, 2010; Pouplier, 2007) or in naturalistic speech (Alderete et al., 2021). However, a recent study failed to find evidence for phonetic distortions in another context in which it would be expected, single word reading aloud of irregular words in which the lexical and sublexical routes generate phonological plans for different vowels (Irons, 2020). The goal of this dissertation is to understand why this discrepancy exists, that is why phonetic distortions are observed in some, but not all cases, in which they are predicted by cascading activation theories of speech production as there are many, potentially critical differences between the paradigms that do and do not observe phonetic distortions. In this dissertation, I present two experiments, one using tongue twisters, and one using picture-word interference, designed specifically to control for differences in errors, scope of planning and word position, to allow us to better understand when a cascade from phonological planning to articulatory implementation can be observed phonetically. Similar to past tongue twister work (Baese-Berk & Goldrick, 2009; Frisch & Wright, 2002; Goldrick, 2016; Goldrick & Blumstein, 2006; Goldrick et al., 2016; Goldstein et al., 2007; McMillan & Corley, 2010; Pouplier, 2007) I observed phonetic distortions, evidence for cascading activation in onset tongue twisters. In nucleus tongue twisters I found that cascading activation might present differently in vowels than it does in consonants. We did not, however, observe phonetic distortions in picture-word interference, therefore open questions remain about how scope of planning and error effects may be responsible for phonetic distortion evidence for cascading activation.
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    Advancing Higher Level Control of Nanoparticle Assemblies Through Ligands
    (2023-08-11) Marolf, David Michael; Jones, Matthew
    The nanoscale size regime is full of potential for the study and development of new functional materials. Many biological materials exist on the nanoscale and can assemble into a variety of complex machinery capable of performing the functions necessary for life to continue. Human-made materials are still far behind what exists naturally, however, over the past few decades, nanoparticles have emerged as a synthetic class of material with intriguing properties making them capable of a large variety of potential applications. One such property is their ability to self-assemble under certain conditions, potentially paving the way to better mimic the high functionality of biological materials. In this thesis, I present research into self-assembling systems of particles that will bring the community closer to true biomimetic materials, primarily through careful use and control of the ligands at the nanoparticle surface. In chapter 1, I detail how ligands affect nanoparticles on multiple levels. First, I discuss how ligands are crucial for the synthesis and growth of a variety of nanoparticles of various compositions and morphologies. Then, I detail how ligands are used to impart functionality to nanoparticles in a variety of different applications. Finally, I discuss how ligands are used to assemble particles, paying special attention to how ligands can be used to assemble nanoparticles in more complex ways such as “lifelike” dissipative self-assembly. In chapter 2, I discuss my findings applying the community’s understanding of functionalization to the functionalization of ultrathin gold nanowires, the highest aspect ratio gold nanoparticle morphology currently known. Through functionalization with a stimuli-sensitive ligand, dynamic systems of nanowires that assemble and disassemble in response to specific stimuli can be obtained. These nanowires can also be assembled into macroscopic fibers, demonstrating preliminary work that could be continued to develop fibers of nanowires as functional materials. In chapter 3, I present my work exploring the study of DNA-functionalized gold nanoprisms and their sharp transitions between an assembled and disassembled state. I explore the origins of these sharp transitions that cannot be explained by contemporary models of similar DNA-functionalized nanoparticles. Finally, in chapter 4, I discuss the challenges the community faces developing synthetic, out-of-equilibrium, dissipative nanoscale self-assembling systems. To characterize such systems even if they can be successfully designed and synthesized, careful consideration must be given to the spatial and temporal resolution available with current analytical techniques along with the inherent advantages and drawbacks of these techniques. Furthermore, as spatial and temporal resolution continues to be improved, the amount of raw data produced per experiment increases at a high rate necessitating the adoption and development of more advanced data analysis techniques. This thesis furthers the field of self-assembly, such that future researchers will be closer to developing synthetic systems with high degrees of complexity capable of precise function that can be targeted towards a variety of applications.
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    On the Design of Reconfigurable Edge Devices for RF Fingerprint Identification (RED-RFFI) for IoT Systems
    (2023-08-11) Keller, Thomas Aidan Flaherty; Cavallaro, Joseph R
    Radio Frequency Fingerprint Identification (RFFI) classifies wireless transmitters by the signal distortions from their unique hardware impairments. RFFI capable receivers can authenticate insecure transmissions without the sender's cooperation, making them well suited for notoriously vulnerable IoT devices. Neural networks have dominated recent RFFI implementations but are prohibitively inflexible for practical use, requiring bespoke models for different transmission schemes and complete retraining for any change in authenticated devices. This along with the high computational and energy requirements for neural network training makes RFFI unfeasible for edge deployment: a primary use case of IoT. To remedy this, we propose the Reconfigurable Edge Device for Radio Frequency Fingerprint Identification (RED-RFFI), a novel FPGA inference framework for RFFI using a programmable Deep-Learning Processing Unit (DPU) to analyze variable length signals for a mutable list of authenticated devices. This approach is uniquely capable of operating on the edge without relying on a high-performance computer for iterative FPGA redesign. Using the Xilinx Vitis AI inference development platform, we implement a state-of-the-art Transformer-based model analyzing LoRa signals as a test case.
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    Emotions and Social Attitudes: Exploring Why Disgust Underlies Conservatism and Prejudice
    (2023-08-11) McDonald, Cayden; Alford, John
    A voluminous literature in political science has found that individuals higher on disgust sensitivity are more likely to be socially conservative, vote for right-wing parties, and hold prejudice towards outgroups. This project seeks to identify the causal mechanism behind these relationships. Each chapter in this project focuses on a different theory: The Behavioral Immune System, Social-Functionalism, and Socially Motivated Cognition. The Behavioral Immune System theory posits that individuals unconsciously tag outsiders as pathogenic threats. I run an experiment to test this. While I find evidence that disease cues cause prejudicial behavior, I find no evidence that outgroup members are seen as pathogenically threatening. The second study examines a Socio-Functionalist account of emotions. This theory argues emotions are designed to solve specific survival problems. Because outgroups can pose different types of threat, individuals should associate them with different emotions. I run an experiment where I manipulate the emotions of fear and disgust. I find that the manipulations are effective at changing emotional states, but they do not change opinions towards outgroups or immigration. I do find that disgust sensitivity and fear sensitivity predict opposition to immigration. However, this opposition is not confined to one domain, as the Socio-Functionalist account suggests. Rather, propensity to feel these emotions predicts opposition to all forms of immigration. Finally, I examine the theory of Socially Motivated Cognition that holds that individuals adopt political ideologies to manage emotional and epistemic needs. I argue that disgust may create a need for avoidant behavior, and that this desire to avoid novel and dangerous entities will translate into social conservatism. Using a Beanfest game I fail to find that disgust (state or trait) leads to avoidant behavior. In total, this project examines some of the most common theories for why disgust links to social attitudes, but fails to find evidence for any of them. I conclude with suggestions for future research.
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    Igneous life cycles: geochemistry of magma from mantle to surface and back again
    (2023-08-11) Allen, Sydney Marie; Lee, Cin-Ty
    Material from within the Earth is cycled and recycled from the interior of the Earth to the surface in igneous rocks. The chemistry of igneous rocks record snapshots of this complex history. Here, we use three major projects to assess important processes in this life cycle. Continental arc volcanism generates a wide diversity of magma compositions, but the tempos of compositional variation are unclear. Here, we investigate a 7-million year record of volcanic ash layers in the Cretaceous Eagle Ford Group to investigate temporal changes in ash composition on <100 kyr timescales. We apply an empirical Ti/Zr-SiO2 relationship to Ti/Zr measurements of 52 Eagle Ford bentonites to reconstruct of ash protolith SiO2 of altered bentonites. Ash compositions fluctuate between periods of high and low silica volcanism over ~100 kyr timescales. If the temporal variability of these ashes represents broad snapshots of the Cordilleran continental arc, these results suggest that continental arc systems may undergo episodic changes in the extent of magmatic differentiation or the nature of eruption on rapid (<100 kyr) timescales. Slow-slip megathrust events in the Hikurangi forearc region, New Zealand, may be related to seamount subduction. We examine differences in the clast origins, depositional settings, and diagenetic histories of volcaniclastic units to highlight the heterogeneity of volcanic systems on the Hikurangi Plateau. The presence of voluminous hydrous clays within thick, altered volcaniclastic units provides a ready source for excess pore fluids that may enable slow-slip events along the Hikurangi subduction zone. Alkaline magmatism at Mountain Pass, CA has attracted attention due to its spatial and temporal association with a REE-rich, economically important carbonatite. However, questions remain about the origins of magma here. We present geochemical data for 121 primitive alkaline igneous rocks to allow a more complete picture of these uncommon igneous compositions. Examining primitive magma composition affords a glimpse into the early stages of magma generation to understand the origins and early histories of alkaline magmatism here. We argue for the importance of pyroxenite melting and suggest that metasomatism related to earlier subduction in this region were significant influences on mama compositions.
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    Flash Joule heating for nanomaterials synthesis, waste upcycling, and hydrogen production
    (2023-08-11) Wyss, Kevin Michael; Tour, James M; Weisman, Bruce
    Many sustainable technologies, such as chemical recycling of waste plastics or the low-carbon intensity production of clean-burning hydrogen gas, have existed for decades. However, despite current political and societal initiatives to minimize plastic waste or transition to hydrogen energy sources, little global progress has been made in their widescale adoption. Over-complexity or critical shortcomings in the economic viability and scalability of these processes often limit their industrial implementation and overall impact. Similarly, although hailed a 21st century ‘wonder-material’, graphene has followed a related trajectory because of the same limiting factors. Flash Joule heating represents a new strategy that can be adapted to address many applications including plastic recycling or upcycling, low-carbon intensity hydrogen production, and graphene synthesis. Flash Joule heating is scalable, low in process complexity, and affords low-cost, efficient, and environmentally friendly production of high-value nanomaterials. This thesis begins by introducing current industrial graphene production methods and applications in chapter 1. Chapters 2-4 highlight the synthesis, characterization, and application of turbostratic graphene from amorphous carbonaceous feedstocks. In chapter 2, simple flash Joule heating synthesizes graphene from waste materials such as ash resulting from the chemical recycling of plastics. The graphene quality is optimized and characterized, and the value of the produced graphene is demonstrated as a reinforcing additive in various composite applications. In chapter 3, graphene with varying 13C/12C isotopic content is prepared, up to 99% 13C content, which results in unexpected spectroscopic findings. In chapter 4, graphene is formed from mixed waste plastics, with quantified efficiency and tabulated environmental burdens, and compared to current industrial methods, using a perspective life-cycle assessment. Taking inspiration from chemical vapor deposition and different bottom-up reaction strategies, other exciting classes of graphitic carbon nanomaterials can be synthesized using flash Joule heating. Holey and wrinkled graphene with significantly increased surface area is synthesized from mixed waste plastics in chapter 5, and applied in electrocatalytic and energy-storage applications. A similar material can be synthesized in a scalable manner using simple alkaline salt templating, and used for water purification applications, as demonstrated in chapter 6. Carbon nanotubes, nanofibers, and hybrid 1-dimensional and 2-dimensional materials can also synthesized through the in situ formation of catalytic growth nanoparticles, upcycling mixed waste plastic to outperform carbon nanotubes and graphene in composite applications, with significant improvements in environmental impact as compared to current carbon nanotube production methods. Lastly, in chapter 8, production of clean hydrogen gas from waste plastic at zero net-cost is demonstrated, due to the co-production of high-value graphene. Through process optimization, flash Joule heating of plastics, with no added catalyst, the highest yet-published yields of hydrogen gas from plastics is achieved and demonstrated for all common consumer waste plastics. Life-cycle assessment and techno-economic analysis demonstrate that the flash Joule heating hydrogen production strategy releases less CO2 than all current methods excluding electrolysis, while affording extreme cost-competitiveness for hydrogen production. Further, through study of the reaction intermediates and other volatiles coupled with thermodynamic and molecular dynamics simulations, the seed-growth, bottom-up hypothesis of graphene formation during flash Joule heating can be further substantiated.
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    Transforming Covalent Organic Framework Synthesis for Advanced Applications: From Solution Processing to High- Throughput Production in Flow Reactors
    (2023-08-10) Khalil, Safiya; Verduzco, Rafael
    Water and energy are essential for sustaining life on earth. As the population grows and living standards improve, the demand for clean water and energy continues to rise simultaneously. In this regard, fossil-fuel consumption, CO2 emissions and byproduct formation will continue to grow in these industries. Integrating advanced nanomaterials in the water and energy sectors emerges as a pivotal strategy for satisfying global water and energy demands in a secure, affordable, and sustainable manner. In light of the foregoing, My PhD is centered on a newly emerging class of nanomaterials known as covalent organic frameworks (COFs). Owing to their porosity, crystallinity, modularity and tunability, COFs have emerged as attractive candidates for various applications including membrane-based separations, photocatalysis and ion transport. However, their wide-scale implementation is hindered by complications related to their synthesis, upscaling, and processing, which also impedes their commercialization and industrialization. In my thesis, I discuss my attempts to tackle the synthetic, scalability and processability challenges of COFs to accelerate their commercialization and facilitate their employment in the water and energy sectors to help us meet escalating demands securely, affordably, and sustainably.
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    Using methyl halides as a reporter in a model soil consortium and for intercellular signaling
    (2023-08-08) Lu, Li Chieh; Silberg, Jonathan
    Over the past decades, there has been an increasing understanding of the important and diverse role played by the soil microbiome in maintaining soil health, plant productivity, and biogeochemical cycles. Understanding the precise nature and contribution of these roles can allow us to harness soil microbial communities for agriculture, environmental engineering, and bioremediation. While -omics approaches and other bulk measurements have provided insights into soil microbial communities and their composition, these attempts can be confounded by a lack of suitable tools for understanding the perception and responses of individual microbes to different events and community members in soil. In this thesis, I review applications of synthetic biology to address some of the aforementioned challenges in researching and applying soil microbial communities. Then, I describe my work in evaluating and expanding the use of gas-output microbial biosensors in individual soil bacterial species and in a soil bacterial consortium via a gas-mediated cell-cell signaling relay. Additionally, I describe the construction of safe soil habitats for synthetic biology that allow us to evaluate intercellular microbial interactions and gas-output biosensor applications at centimeter- and meter-length scales. I also describe my efforts at constructing novel biosensor inputs for gas-output microbial biosensors and characterizing these new biosensors in liquid and soil environments. Finally, I discuss avenues for expanding on my work by applying gas-output microbial biosensors in more realistic soil conditions to answer fundamental soil science questions.
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    Development of Extracellular Matrix-Based Biomaterials for Musculoskeletal Tissue Engineering
    (2023-08-08) Hogan, Katie JoAnna; Mikos, Antonios G
    Extracellular matrix (ECM)-based materials, which provide tissue-specific biochemical cues for cell recruitment, proliferation, and differentiation, have been the subject of significant research for cartilage, bone, and muscle tissue engineering. The use of advanced fabrication techniques such as 3D-printing (3DP) and electrospinning enable the fabrication of scaffolds with macro- and microarchitecture that further aids in these applications. In the initial aims of this thesis, decellularized cartilage ECM (cdECM) and demineralized bone matrix (DBM) were adapted into composite colloidal 3DP inks for the fabrication of 3DP constructs with tunable tissue-specific ECM content and photocrosslinking for cartilage and bone regeneration. First, photo-reactive cdECM was combined with photo-reactive gelatin nanoparticles (GNPs) in composite hydrogel-colloidal composite inks. Increased GNP content increased cdECM-GNP ink printability, and increased photocrosslinking was found to decrease cdECM-GNP scaffold swelling and degradation rates and increase biomolecule retention, demonstrating control over scaffold physicochemical properties. Next, photo-reactive DBM nanoparticles (DBM-NPs) were synthesized and combined with photo-reactive GNPs to create colloidal composite 3DP inks and scaffolds. The addition of DBM-NPs into composite colloidal inks did not impact ink printability, and photocrosslinking was demonstrated to decrease scaffold swelling and degradation kinetics, showing the tunability of these properties. An in vitro assessment of mesenchymal stem cell osteogenesis showed the osteoconductivity of DBM-NP-incorporating 3DP constructs. In the final component of this thesis, electrospun aligned decellularized skeletal muscle ECM (mdECM) microfiber meshes with variable crosslinking densities were implanted in an in vivo rat model of volumetric muscle loss, and increased crosslinking was associated with increased expression of markers for angiogenesis and myogenesis. This difference was thought to be related to more prolonged release of biochemical cues over time, emphasizing the importance of crosslinking in controlling presentation of mechanical and biochemical cues. Together, these studies present a variety of strategies for adapting ECM-based materials for high-throughput, precise fabrication methods suitable for the tissues of interest. The completion of this thesis and development of these techniques has resulted in fabrication platforms for ECM-derived biomaterial scaffolds with crosslinking systems for tunable physicochemical properties and biomolecule presentation which have broad applications across the field of tissue engineering.
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    Engineering Surfaces for Sensitive Detection of Analytes
    (2023-08-11) Niu, Sunny; Biswal, Sibani L
    Engineering functional surfaces and tuning their properties has significant implications that allow us to harness their potential in addressing relevant scientific challenges. The work presented in this thesis investigates the intelligent design of micro- and nanoscale surfaces and their interactions with biomolecular and SERS-active analytes in sensing applications. In the first part of this thesis, the numerous surface interactions involved in a biosensor are investigated and optimized to produce a device for detection of blood-based biomarkers of traumatic brain injury. The next body of work presents an alternate sensing platform that also takes advantage of the surface properties of plasmonic, nanoscale materials and their interaction with light. Finally, a novel methodology for surface-sensitive investigation of proteins using ToF-SIMS is presented. Collectively, this work aims to harness interactions at surfaces and interfaces to create novel, functional solutions to sensing challenges.
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    New Frontiers in Quantum Simulation of an Extended Dicke Model and Active Cooling
    (2023-08-08) Marquez Peraca, Nicolas; Kono, Junichiro
    Groundbreaking discoveries in the fields of light-matter interactions and thermoelectrics in the past two decades have profoundly shaped our understanding of how photons, electrons, and phonons interact. Increased control over the quality of engineered systems, novel measurement techniques, and quantitative improvements in theory are the driving force behind modern, record-high values of light-matter coupling strength and thermoelectric performance. In this work, I bring together experimental and theoretical techniques to study the interplay between magnons and spins in ErFeO3, photons and plasmons in Fischer nanostructures, and electrons and phonons in thermoelectric active cooling materials. Specifically, I perform terahertz time-domain magneto-spectroscopy measurements on the rare-earth orthoferrite ErFeO3 as a function of temperature and magnetic field, and we propose a novel protocol that uses this material as a solid-state quantum simulator of an extended Dicke model. Then, I conduct aperture-based scanning near-field optical microscopy measurements on Fischer nanostructures, and observe field enhancement and localization with resolution beyond the diffraction limit. Lastly, I study active cooling under arbitrary external thermal resistances, and map out the regions where active cooling is advantageous compared to Carnot-limit refrigeration. These results lead to a deeper understanding of fundamental interactions in magnetic, semiconducting, and low-dimensional materials, and further motivate translating research into engineering solutions.
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    Molecular Modeling of Nonionic Surfactant Micellar Systems in Aqueous Solutions
    (2023-07-31) Lu, Jinxin; Chapman, Walter G.
    Surfactants are amphiphilic molecules consisting of both hydrophobic and hydrophilic groups. The unique structure of surfactants and their ability to self-assemble into interesting microstructures lead to extensive application in industrial and commercial fields. The study of their interfacial phenomena and self-assembling behavior has also been of interest to academic researchers for years. One key that led to the wide application of surfactant micelles is their ability to enhance the solubility of hydrophobic compounds in water. However, there is a lack of thorough theoretical understanding of the micellar structure and solubilization process in solution due to its inhomogeneous nature. Also, wide industrial application leads to continued interest in the development of predictive theoretical models to understand the system comprehensively and guide the design of optimal surfactant solutions. This thesis aims to develop a thermodynamic model for surfactant self-assembly in solution. A molecular density functional theory (DFT) that accounts for molecular structure, van der Waals attraction, and hydrogen bonding, i.e., interfacial statistical associating fluid theory (iSAFT), is applied to study the fluid structure and phase behavior of nonionic surfactant micellar systems, with particular interest in understanding the partitioning of solute into the micelle. The model predicts the macroscopic physical properties and provides an explanation of the microscopic density profile. This work aims to provide a reliable tool that can be used in surfactant design and material screening. Key contributions of this thesis include: 1. A quantitative iSAFT approach to model polyethylene oxide alkyl ether surfactant micelle formation in water and to model the effect of surfactant architecture on micelle properties and solute partitioning. The effects of size and branching of surfactant head and tail groups on micelle size distribution are also studied. 2. The iSAFT approach is applied further to predict the partition equilibrium behavior between micelles and various solutes. The model is able to predict properties such as partition coefficient and, at the same time, explain the exact solute partitioning behavior at the microscopic level. The mechanism behind the competitive solubilization of benzene and hexane is also studied. 3. The role of alcohol as an additive in the surfactant micellar system is investigated. The dualistic effect of alcohol as both a cosolvent and a cosurfactant is captured, and the model predictions are in agreement with experimental results. The change in behavior with changing alcohol carbon numbers is also studied and discussed.
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    Using synthetic biology to record information in DNA and RNA within wastewater microbes and communities
    (2023-08-02) Kalvapalle, Prashant Bharadwaj; Stadler, Lauren B.; Silberg, Jonathan J.
    Microorganisms form the bedrock of key ecological processes that make the Earth habitable. Microbial communities regulate carbon and nitrogen cycles, influencing greenhouse gas concentrations and agricultural productivity. As such, understanding these microbial processes is critical to address climate change and food security and to advance sustainable practices. Microbial communities within wastewater are also critical to public health, such as through the exchange of genetic material, which can result in more virulent pathogens, and resistance to known antibiotic treatments. Engineered microbial sensors can be developed to gather information and understand the influence of physicochemical conditions of the environment. To date, the majority of biosensors developed rely on fluorescent outputs, which are challenging to apply in environmental matrices that are opaque, and contain autofluorescent particles or microbes. In addition, few biosensors have been applied over timescales relevant to ecological processes, and there is a need for biosensors that function over week-long timescales in situ. In this thesis, I describe biosensors that record signals by modifying DNA and RNA, which are designed to monitor chemical exposures and gene exchange within natural environments, respectively. I benchmark the performance of these sensor systems within undomesticated, wastewater microbes. I demonstrate that the DNA biosensor can record analog information about the exposure to a sugar arabinose and microbial communication molecule 3-oxo-C12-homoserine lactone. I describe strategies that can be used to allow these DNA memory biosensors to record information during 9 day incubations. Additionally, I demonstrate that a new type of RNA memory sensor is able to function in a wide variety of wastewater taxa, which writes information in 16S ribosomal RNA. In the first proof-of-concept experiments, I show this sensor can record information in more than 100 microbes in parallel. Together, the tools extend the tools available to environmental microbiologists for detecting microbial processes in complex environments, leading to insights of environmental and public health importance. The longer duration DNA biosensor will be useful for studying the bioavailability of chemicals in situ, while the community distributed RNA memory sensor will be useful for identifying the taxonomic range of gene transfer recipients in a high-throughput manner.
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    Advancement of fiber image guide based snapshot imaging spectrometer technology for bioimaging and environmental applications
    (2023-08-08) Flynn, Christopher; Tomasz Tkaczyk, Tomasz
    Hyperspectral imaging spectrometers provide detailed and continuous spectral data in addition to spatial information found in commercial RGB or monochromatic cameras. The addition of spectral information can provide valuable insight in many fields such as but not limited to biomedical imaging, smart farming, environmental monitoring, and remote sensing. Key to monitoring dynamic events is fast, snapshot acquisition of the hyperspectral datacube and then quick turnaround of raw data into decipherable hyperspectral images and spectra. Previous implementations of fiber based imaging spectrometers were focused on breadboard proof of concept designs and were not optimized for field imaging. This thesis details the development of two generations of imaging spectrometers for remote sensing of crop health and the advancement of fiber image guide based snapshot imaging spectrometer technology including fiber bundle fabrication, system level integration and ruggedization, and in-the-field application based data collection. Examples of remote sensing data for smart farming with spectral data informing plant stress from abiotic stressors such as water stress and soil minerology are presented. Design and implementation of components and housing will enable the snapshot imaging spectrometers to image dynamic targets in a variety of environments, including from an aerial platform. To enable miniaturization and high level integration, optical fiber fabrication using 2-photon 3D printing is presented. 2-photon fabrication of fiber bundles was pursued via investigation of individual fibers and fiber components such as fiber couplers, then small arrays in air, and then scale up and the addition of cladding.
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    Language Support for Real-time Data Processing
    (2023-08-11) Kong, Lingkun; Mamouras, Konstantinos
    Recent technological advances are causing an enormous proliferation of streaming data, i.e., data that is generated in real-time. Such data is produced at an overwhelming rate that cannot be processed in traditional manners. This thesis aims to provide programming language support for real-time data processing through three approaches: (1) creating a language for specifying complex computations over real-time data streams, (2) developing software-hardware co-design to efficiently match regular patterns in a streaming setting, and (3) designing a system for parallel stream processing with the preservation of sequential semantics. The first part of this thesis introduces StreamQL, a high-level language for specifying complex streaming computations through a combination of stream transformations. StreamQL integrates relational, dataflow, and temporal constructs, offering an expressive and modular approach for programming streaming computations. Performance comparisons against popular streaming engines show that the StreamQL library consistently achieves higher throughput, making it a useful tool for prototyping complex real-world streaming algorithms. The second part of this thesis focuses on hardware acceleration for regular pattern matching, specifically targeting the matching of regular expressions with bounded repetitions. A hardware architecture inspired by nondeterministic counter automata is presented, which uses counter and bit vector modules to efficiently handle bounded repetitions. A regex-to-hardware compiler is developed in this work, which provides static analysis over regular expressions and translates them into hardware-recognizable programs. Experimental results show that our solution provides significant improvements in energy efficiency and area reduction compared to existing solutions. Finally, this thesis presents a novel programming system for parallelizing the processing of streaming data on multicore CPUs with the preservation of sequential semantics. This system addresses challenges in preserving the sequential semantics when dealing with identical timestamps, dynamic item rates, and non-linear task parallelism. A Rust library called ParaStream is developed to support semantics-preserving parallelism in stream processing, outperforming state-of-the-art tools in terms of single-threaded throughput and scalability. Real-world benchmarks show substantial performance gains with increasing degrees of parallelism, highlighting the practicality and efficiency of ParaStream.
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    Coating Displacement Studies on Single-Wall Carbon Nanotubes
    (2023-08-09) Lei, Kunhua; Weisman, Bruce R.
    We have investigated the process by which coatings of sodium dodecyl sulfate (SDS) adsorbed on the surface of single-wall carbon nanotubes (SWCNTs) are replaced by short oligomers of single-stranded DNA (ssDNA). The kinetic and equilibrium measurements focused on the influence of ssDNA length, concentration, SWCNT structure, and temperature. Our experiments involved samples of SWCNTs dispersed in a low concentration aqueous solution of SDS, to which we injected specific amounts of ssDNA solution, using oligomers composed of from 3 to 20 GT nucleobase units. We used absorption and emission spectroscopy to monitor the displacement process and measured time-dependent fluorescence spectra for kinetic studies. Our results show that the SDS coating displacement kinetics have a strong inverse dependence on the length of the ssDNA oligomer. Moreover, for displacement by ssDNA oligomers such as (GT)5, the initial rate constant depends not only on nanotube diameter but also on nanotube chiral angle. We further found that higher temperatures and higher ssDNA concentrations lead to faster displacement kinetics. Based on the experimental results, we propose a two-step displacement mechanism in which disruption of the initial SDS coating is followed by conformational relaxation of the newly adsorbed ssDNA. The first step is rate-determining for short oligomers whereas the second step becomes rate-determining for longer oligomers. In addition, we conducted equilibrium coating displacement experiments that measured stable spectral shifts of the emission peaks from multiple nanotube species resulting from the calibrated addition of ssDNA to aqueous suspensions of SWCNTs in SDS. Data were compiled to construct “titration” curves showing diameter-dependent inflection points at which the nanotubes were equally coated by SDS and the ssDNA. Smaller diameter nanotubes showed coating displacement at significantly lower ssDNA concentrations as compared to larger diameter nanotubes. Finally, this differential coating affinity result was applied in the development of a new structural sorting method that successfully separated smaller from larger diameter SWCNTs through simple steps including filtration. Last but not the least, we studied the steady-state emission spectra of stirred SWCNTs samples and built a model that interpreted the relationship between emission intensity and stirring rate. We found that stirring increases the emission intensity of SWCNT samples. This is attributed to a relatively slow photo-induced oxidation process on SWCNTs that partially quenched their emission. However, rapid stirring replaces photo-oxidized nanotubes in the probed volume with fresh nanotubes from the surrounding solution and restores the unquenched emission intensity.
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    Uncovering Genes Responsible for Mitochondrial Maintenance and Surveillance
    (2023-07-27) Moreno, Armando; Kirienko, Natasha
    Mitochondria are key organelles for cellular health and metabolism and the activation of programmed cell death processes. Although pathways for regulating and re-establishing mitochondrial homeostasis have been identified over the past twenty years, the consequences of disrupting genes that regulate other cellular processes, such as division and proliferation on affecting mitochondrial function remain unclear. Using a cancer cell line mutation database, I developed a set of 139 genes in Caenorhabditis elegans predicted to play roles in mitochondrial maintenance or function. Disruption of a sample of genes from this set caused phenotypes consistent with mitochondrial dysfunction, including increased fragmentation of the mitochondrial network, abnormal steady-state levels of NADH, or ROS, or altered oxygen consumption. RNAi-mediated knockdown of these genes often also exacerbated α-synuclein aggregation in a C. elegans model of Parkinson’s disease. This gene set provides a foundation for identifying new mechanisms that support mitochondrial and cellular homeostasis and can be potentially used in targeted therapeutics of diseases such as cancer and neurodegenerative disease. In addition to the genes mentioned above, mitochondrial surveillance mechanisms are also essential for healthy mitochondrial function. These mechanisms are in place to ameliorate the deleterious effects of faulty protein import, increase in oxidative stress, and bioenergetic disruption. While some regulators for the ESRE (Ethanol and Stress Response Element) mitochondrial surveillance network have been identified in the past, a transcription factor specific to ESRE regulation has not been identified. Through a high-throughput screen, I discovered F23B12.7, a bZIP transcription factor, as an ESRE regulator. F23B12.7 is necessary for proper ESRE activation in C. elegans and is necessary for survival during Pseudomonas aeruginosa infection. This transcription factor is also necessary for protection against mitochondrial damaging agents such 1,10-Phenanthroline. F23B12.7 also shows regulation of both box C/D and box H/ACA snoRNP complexes (known for their role in ribosome biogenesis). This discovery opens a new avenue of research of the interplay between ribosomal biogenesis and mitochondrial health. Further understanding of these mitochondrial surveillance networks will also provide insight into how these mechanisms react to stress or infection and can be potential targets of treatment for mitochondrial related diseases.