Now showing items 1-20 of 2297

    • Stability and Asymptotics in Electrohydrodynamics

      Alves, Nuno J. (2023-09-12) [Dissertation]
      Advisor: Tzavaras, Athanasios
      Committee members: Gomes, Diogo A.; Bagci, Hakan; Markowich, Peter A.; Lattanzio, Corrado
      This dissertation focuses on the relative energy analysis of two-species fluids composed of charged particles. It presents a formal derivation of the relative energy identity for both the bipolar Euler-Maxwell system and the unmagnetized case of the bipolar Euler-Poisson system. Furthermore, the dissertation explores several applications of the relative energy method to Euler-Poisson systems, enabling a comprehensive stability analysis of these systems. The first application establishes the high-friction limit of a bipolar Euler-Poisson system with friction, converging towards a bipolar drift-diffusion system. Moreover, the second application investigates the limits of zero-electron-mass and quasi-neutrality in a bipolar Euler-Poisson system. In the former limit, a non-linear adiabatic electron system is obtained, while the combined limit yields an Euler system. A weak-strong uniqueness principle for a single-species Euler-Poisson system in the whole space is also established. This principle is further extended to an Euler-Riesz system, considering a more general interaction potential. The theory of Riesz potentials, along with representation formulas for the potentials, is employed to overcome the technical challenges in these studies.
    • Extreme-Value Models and Graphical Methods for Spatial Wildfire Risk Assessment

      Cisneros, Daniela (2023-09-11) [Dissertation]
      Advisor: Huser, Raphaël
      Committee members: Ombao, Hernando; Parsani, Matteo; Mateu, Jorge
      The statistical modeling of spatial extreme events, augmented by graphical models, provides a comprehensive framework for the development of techniques and models to describe natural phenomena in a variety of environmental, geoscience, and climate science applications. In a changing climate, the impact of natural hazards, such as wildfires, is believed to have evolved in frequency, size, and spatial extent, although regional responses may vary. The aforementioned impacts are of great significance due to their association with air pollution, irreversible harm to the environment and atmosphere, and the fact that they put human lives at risk. The prediction of wildfires holds significant importance within the realm of wildfire management due to its influence on the allocation of resources, the mitigation of detrimental consequences, and the subsequent recovery endeavors. Therefore, the development of robust statistical methodologies that can accurately forecast extreme wildfire occurrences across spatial and temporal dimensions is of great significance. In this thesis, we develop new spatial statistical models, combined with popular machine learning techniques, as well as novel extreme-value methods to enhance the prediction of wildfire risk using graphical models. First, in order to jointly efficiently model high-dimensional wildfire counts and burnt areas over the whole continguous United States, we propose a four-stage zero-inflated bivariate spatiotemporal model combining low-rank spatial models and random forests. Second, to model high values of the McArthur Forest Fire Danger Index over Australia, we develop a novel spatial extreme-value model based on mixtures of tree-based multivariate Pareto distributions. Our new methodology combines theoretically justified spatial extreme models with a computationally convenient graphical model framework to spatial problems in high dimensions efficiently. Third, we exploit recent advancements in deep learning and build a parametric regression model using graphic convolutional neural networks and the extended Generalized Pareto distribution, allow us to jointly model moderate and extreme wildfires observed on irregular spatial grid. We work with a novel dataset of Australian wildfires from 1999 to 2019, and analyse monthly spread over areas correspond to Statistical Area Level 1 regions. We highlight the efficacy of our newly proposed model and perform risk assessment for Australia and dense communities.
    • Mean Field Games price formation models

      Gutierrez, Julian (2023-09-06) [Dissertation]
      Advisor: Gomes, Diogo A.
      Committee members: Cirant, Marco; Jasra, Ajay; Alouini, Mohamed-Slim
      This thesis studies mean-field games (MFGs) models of price formation. The thesis focuses explicitly on a MFGs price formation model proposed by Gomes and Saude. The thesis is divided into two parts. The first part examines the deterministic supply case, while the second part extends the model to incorporate a stochastic supply function. We explore different approaches, such as Aubry-Mather theory, to study the properties of the MFGs price formation model and alternative formulations using a convex variational problem with constraints. We propose machine-learning-based numerical methods to approximate the solution of the MFGs price formation model in the deterministic and stochastic setting.
    • Thermal and Plasma Processing of Orthorhombic Gallium Oxide Films for Optoelectronic Applications

      Banda, Yara S. (2023-09) [Thesis]
      Advisor: Ooi, Boon S.
      Committee members: Ohkawa, Kazuhiro; Mohammed, Omar F.
      Gallium oxide (Ga2O3) has been the subject of extensive research activity due to its ultrawide bandgap and large breakdown field, which make it promising for next-generation applications in deep ultraviolet detection and power electronics. β-Ga2O3 is the most thermally stable and well-studied polymorph of Ga2O3. However, during the past decade, the metastable orthorhombic κ-Ga2O3 has emerged as an equally impressive candidate material owing to its high crystal symmetry and ferroelectric and spontaneous polarization properties. Several studies have reported the growth and characterization of κ-Ga2O3 films using different epitaxial growth methods. However, the existing literature still lacks reports on the processing of this material for future device applications. Therefore, in this thesis, we investigate the effects of high-temperature treatment and plasma exposure on the structural and optical properties of mist chemical vapor deposition (mist-CVD)-grown κ-Ga2O3 films. Using high-temperature X-ray diffraction (HT-XRD), we show that the films remain phase-pure up to an annealing temperature of 800 ˚C, after which β-phase peaks start to appear and eventually show a complete transition to β-Ga2O3 at 875 ˚C. Additionally, we show using detailed high-resolution transmission electron microscopy (HRTEM) and XRD analyses that annealing at 700 ˚C in ambient air is effective in improving the crystal quality of the κ-Ga2O3 layer by relieving in-plane strains and epitaxial stacking faults. Moreover, since dry etching is needed for the anisotropic patterning of materials for device applications, it is necessary to investigate the effects of plasma exposure on the near-surface properties of the material in order to keep its damage to a minimum. Therefore, we studied the impacts of plasma exposure during dry etching on the chemical structure, crystallinity, and optical properties of κ-Ga2O3 by using a variety of characterization methods. We observed how varying the etching parameters using BCl3/Ar can affect the near-surface properties of the material, which play a key role in modifying the performance of future devices. Specifically, we found that both RIE/ICP power and BCl3/Ar ratio can influence the surface stoichiometry and the concentration of native defect density, which affect the material’s structural and optical properties. Additionally, we reported for the first time on κ-Ga2O3 ICP-RIE process optimization using a BCl3/Ar gas mixture. By tuning the process parameters, the optimized recipe had a high etch rate of 130 nm/min, showed a surface roughness reduction of 56%, and produced vertical sidewall profiles for ridge device structures.
    • Advances in Computational Cryo-Electron Tomography ---Model-based and Neural Reconstructions

      Wang, Yuanhao (2023-09) [Dissertation]
      Advisor: Heidrich, Wolfgang
      Committee members: Ghanem, Bernard; Viola, Ivan; Ropinski, Timo
      Tilt-series cryo-electron tomography (cryo-ET) is an established imaging technique used in several fields like biology and material science. Despite its success, cryo-ET remains an arduous task. The missing-wedge acquisition, the motion, and the high-level noise are the main challenges existing in this field. In this dissertation, we tackle these challenges through the exploration of three distinct approaches: plug-and-play approach, adaptive differentiable density grids, and adaptive tensorial density field representation. Firstly, using embedded fiducial markers, our framework first estimates the motion field in the sample in order to correct the captured projections, and then reconstructs the sample using an iterative plug-and-play approach. Secondly, we propose an adaptive representation based on an octree structure. Each block of the structure represents a 3D density grid that is optimized from the captured projections. To ensure a denoised output, we update the octree in a multi-scale fashion. We also combined the differentiable image formation model with cross-nodes non-local constraint, total variation, and boundary consistency priors in the loss function. Thirdly, we propose an adaptive tensorial density field representation. Considering that cryo-ET is thin along the z-axis, we use a quadtree structure instead of initializing a nulled octree, and represent each node with a vector-matrix factorization. Combined with total variation, boundary consistency, and an isotropic Fourier prior, our framework allows us to reconstruct clean cryo-ET results. Experiments show considerable improvement in cryo-ET reconstructions.

      Benitez, Marcelo (2023-08-29) [Dissertation]
      Advisor: Hoteit, Hussein
      Committee members: Mishra, Himanshu; Finkbeiner, Thomas; Espinoza, Nicolas; Santamarina, Carlos; Liu, Qi
      The energy demand has increased dramatically in the last century, and so to have global CO2 emissions. Two critical challenges for the geo-energy sector are to develop different approaches for harvesting energy and to actively decrease atmospheric CO2 emissions. Addressing these challenges requires efficient, sustainable, and affordable technical solutions. Complex fluids are ubiquitous and offer great potential for geo-engineering applications such as the development of geo-energy, enhanced oil recovery and CO2 geological sequestration and utilization. This thesis will present new results on interfacial phenomena in CO2-fluid-mineral systems, including interfacial tension hysteresis, the effects of surface-active components on interfacial tension (surfactants, nanoparticles, organo-bentonites and asphaltenes), and the interfacial pinning of immiscible fluids on substrates. Pore-scale phenomena come together in the study of the physical properties of CO2 and its implication for both storage and assisted gravity oil drainage. Finally, we provide a better understanding of the interfacial phenomena of complex fluids and their interactions within porous media that can lead to efficient and sustainable geo-energy systems.
    • Proliferating Cells Encapsulated in Extracellular Matrix-Like Peptide Scaffolds Dynamically Change the Mechanical Properties of the Scaffold

      Rawas, Ranim (2023-08-24) [Thesis]
      Advisor: Hauser, Charlotte
      Committee members: Pain, Arnab; Mahfouz, Magdy M.
      The extracellular matrix, or ECM, is a three-dimensional network that serves as a structural scaffold for tissue construction. To do so, cells need to attach, proliferate, self-organize, and coordinate biochemical deposition across multiple length and time scales. Hydrogels have been utilized as biomaterials because their chemical and mechanical properties can be designed to mimic those of native ECMs. Short, synthetic, amphiphilic peptides have been used to design scaffolds for tissue engineering because the peptides self-assemble in water and are easy to tune. To date, hydrogels for tissue engineering have typically sacrificed one or more crucial properties in favor of improving others, since nearly all chemical and mechanical properties within a hydrogel are interdependent. The focus of this research is to study the mechanical tunability and viability of ultrashort peptide hydrogels derived from naturally occurring amino acids (IIZR, IIZK, and IZZK), such that ideal concentrations of each peptide can be configured to mimic the mechanical properties of native ECMs for human dermal fibroblasts (HDFns) and primary cortical neurons (CNs). Our results show that IIZR, IIZK, and IZZK hydrogel scaffolds are good candidates for these cell types because their stiffness, elasticity, and biocompatibility are commensurate with those of these cells’ native ECMs. As evidence, the stiffness of the materials generally increased with HDFns across all concentrations, except for 2mg/ml. In particular, HDFns favored hydrogels consisting of higher peptide concentrations, resulting in greater elasticity and higher stiffness. IIZR hydrogels were also well-suited for both HDFns and CNs, which could have been due to the peptides’ positively charged R groups that can facilitate cell adhesion via electrostatics.
    • The Influence of Marangoni Flow, Curvature Driven Drainage, and Volatility on the Lifetime of Surface Bubbles

      Aladsani, Abdulrahman (2023-08-24) [Thesis]
      Advisor: Truscott, T. T.
      Committee members: Daniel, Dan; Hoteit, Hussein
      This study investigates the factors that affect the lifetime and popping location of surface bubbles. The experiment was conducted using three different liquids (water, Sodium Dodecyl Sulfate, and Decane) with varying bubble sizes, using three different needle sizes. Each setup was tested 50 times. For pure water bubbles, the foot of the bubble is the most critical location because it typically has the highest temperature gradient, which creates a localized Marangoni flow that thins the film and eventually leads to the bubble bursting at the foot. When SDS was added to water, the bubble lifetime increased significantly. This is because the Marangoni stresses were reduced, and the bubble film thinned mainly due to curvature-driven drainage flow. The lifetime of the SDS bubble had a positive correlation with increasing bubble size. For Decane bubbles, the volatility of the liquid plays a significant role in the lifetime and popping location of the bubble. When the Decane was heated to 40°C, the lifetime of the bubbles increased significantly from 0-20 seconds to 8-12 minutes. This is because the high volatility of the Decane caused rapid evaporation of the bubble cap at the interface, which cooled the surface of the liquid. This temperature difference creates a difference in surface tension, which causes the liquid to flow from the bulk liquid into the apex of the bubble, thickening the cap film until it cools down. Then, it pops from the top due to the curvature-driven drainage.
    • A study of the Root meristem control by the Retinoblastoma-related protein and the effect of beneficial and pathogenic bacteria on root growth

      Castillo Hernandez, Tatiana (2023-08-24) [Thesis]
      Advisor: Blilou, Ikram
      Committee members: Wulff, Brande B. H.; Frøkjær-Jensen, Christian
      Roots are considered an important organ as they transport nutrients and water and provide anchor and support in the plants. The development of roots involves the participation of specific proteins such as RETINOBLASTOMA-RELATED (RBR) which has been found to play a role in cell cycle regulation and stem cell niche maintenance. Additionally, roots can interact with the environment and soil microorganisms that can influence processes in plant growth and development. For instance, plant growth-promoting rhizobacteria (PGPR) have been found to have the ability to alter the root system by their influence on signaling pathways or phytohormones. In this study, we generated RBR mutant lines using CRISPR-Cas9 to determine the role of this protein in early plant growth. We found that the mutant lines contained partial abortion in ovules and mild reduction in siliques suggesting the participation of this protein in the early stages of plant development. Furthermore, we also use beneficial and pathogenic bacteria strains to study their effect on root patterning. We showed that WSC417 beneficial bacteria can influence root structure by promoting the growth of root hairs which might suggest a plant improvement in nutrient uptake. Also, we could observe that WSC417 can exert some protection against DC 3000 pathogenic bacteria when plant seedlings were inoculated with both strains. Overall, we could determine that RBR plays a role in early developmental stages and root development can also be influenced by biotic factors such as microorganisms.
    • Ontogenetic Variability in RNA Quantities in Red Sea Clownfish, Amphiprion bicinctus

      Alaidrous, Wajd (2023-08-22) [Thesis]
      Advisor: Berumen, Michael L.
      Committee members: Gojobori, Takashi; Carvalho, Susana
      Larval dispersal is one of the most complex phenomena that connects populations when larvae migrate over long distances from their native reefs to a new one. Dispersal outcomes are largely variable among individuals, even siblings, and the factors that drive this variability are not understood, making it challenging to create protection plans for marine species. Clownfish, Amphiprioninae, are among the most important coral reef species economically. Thus, creating protection plans for clownfish is necessary, especially as they are under habitat loss threat. Clownfish are considered an optimum model of organisms for studying larval dispersal and population connectivity mainly due to their relatively short larval dispersive phase and ease of breeding them in captivity. Since dispersal traits are influenced by genes, transcriptomic studies can reveal insights into larval dispersal. Thus, the variation in dispersal outcomes could be better understood if the differential expression of genes related to dispersal, such as swimming abilities, are considered. However, there is a lack of knowledge in the basics of gene expression in clownfish larvae. The aim in this thesis is to explore the ontogenic variability in RNA quantities across development in clownfish larvae as a first step of understanding the nature of their gene expression and optimizing RNA extractions and quantifications methods using clownfish as a model organism. We performed an RNA quantification study using larvae of Amphiprion bicinctus clownfish reared at KAUST SeaLabs. This thesis provides some insights regarding the pooled and individual quantities of RNA across time. The optimal pool size and age for various transcriptomic studies was determined. It was concluded that extracting RNA from young larvae is difficult. Depending on the research, it might be necessary to use older larvae or other techniques. The results from this thesis will build the foundation needed as a first step to perform differential gene expression studying the causes of variability in dispersal traits in A. bicinctus and the link between these traits and transcriptomics.
    • Application of Emerging Computational Chemistry Tools to the Study of the Kinetics and Dynamics of Chemical Systems of Interest in Combustion and Catalysis

      Grajales Gonzalez, Edwing (2023-08-21) [Dissertation]
      Advisor: Sarathy, Mani
      Committee members: Schwingenschlögl, Udo; Ruiz-Martinez, Javier; Corchado Martín-Romo, José Carlos
      Despite comprehensive studies addressing the chemical kinetics of butanol isomers, relevant uncertainties associated with the emissions of relevant pollutants persists. Also, a lack of chemistry knowledge of processes designed to produce biofuels limits their implementation at industrial scales. Therefore, the first objective of this thesis was to use cutting-edge kinetic theories to calculate rate constants of propen-2-ol, 1-pronenol, and vinyl alcohol keto-enol tautomerizations, which account for the production of the harmful carbonyl species. The second objective was to use the predictive capabilities of dynamic theories to reveal new chemistry of syngas oxy-combustion in supercritical CO2 and complexities of the zeolite dealumination, two processes involved in coal and biomass conversion. Rate constants computations considered transition state theory with variational effects, tunneling correction, and multistructural torsional anharmonicity. The study also included pressure effects by using and improving the system-specific quantum Rice-Ramsperger-Kassel/modified strong collision model. The atomistic simulations used ReaxFF force fields in hydrogen/oxygen/carbon monoxide/ carbon dioxide mixtures to represent the syngas system and an MFI zeolite with different water loading to model the dealumination. The results show that the studied assisted tautomerizations have much lower energy barriers than the unimolecular process. However, the “catalytic” effect is efficient only if the partner molecule is at high concentrations. Pressure effects are pronounced in the chemically activated tautomerizations, and the improved algorithm to compute pressure-dependent rate constants overcomes the initial difficulties associated with its application to C3 or larger molecules at temperatures above 800-1000 K. Reactive molecular dynamics simulations revealed the role of CO2 as an initiator in the syngas oxy-combustion and a new step involving the formation of formic acid. Those simulations for the zeolite dealumination process also showed that proton transfer, framework flexibility, and aluminum dislodging mediated by silicon reactions are complex dynamic phenomena determining the process. These aspects complement the dealumination theory uncovered so far and establish new paths in the study of water-zeolite interactions. Overall, the rate constants computed in this work reduce relevant uncertainties in the chemical kinetic mechanisms of alcohol oxidation, and the molecular dynamics simulations broaden the chemical knowledge of processes aimed at the utilization of alternative energy resources.
    • Early-stage organoid formation in biofunctionalized self-assembling peptide matrices combinations

      Xu, Jiayi (2023-08-14) [Thesis]
      Advisor: Hauser, Charlotte
      Committee members: Schmidt, Fabian; Al-Sulaiman, Dana
      As the third most commonly diagnosed cancer in the world, colorectal cancer (CRC) has become a pressing and urgent problem, requiring the disease mechanism research and therapeutic development. The field of tissue engineering has considerably progressed since the advent of synthetic matrices for 3D cell culture, providing in vitro models for CRC disease research. Compared to animal-derived matrices such as matrigel, synthetic matrices have several advantages including controllable properties, avoiding ethical problems and batch-to-batch variation. Ultrashort self-assembly peptides of amphiphilic nature have recently proven to be excellent matrices for 3D cell culture of many types of cells. In this thesis, we aimed to use biofunctional peptides to promote the growth of colorectal cancer organoids in the early stage of development. A peptide-based biofunctional hydrogel for organoid culture has been developed for the purpose of establishing a reproducible colorectal cancer model. The hydrogel is composed of self-assembly peptides designed to induce cell-matrix interactions. The hydrogel is mechanically tunable with customizable cell-adhesive ligands and has the ability to promote the formation and growth of colorectal cancer organoids in vitro. One of these biofunctionalized peptide matrices was particularly suitable for CRC lumen development, apical protein expression, and cell differentiation level compared to the gold-standard ECM Matrigel.
    • Low-Power Edge-Enabled Sensor Platforms

      De Oliveira Filho, José Ilton (2023-08-10) [Dissertation]
      Advisor: Salama, Khaled N.
      Committee members: Inal, Sahika; Ahmed, Shehab; Sonkusale, Sameer
      On-site sensing systems provide fast and timely information about a myriad of applications ranging from chemical and biological to physical phenomena in the environment or the human body. Such systems are embedded in our daily life for detecting pollutants, monitoring health, and diagnosing diseases. Especially in the field of health care, the development of portable and affordable diagnosing systems, also known as point-of-care (PoC) devices, is a major challenge. Moreover, to this day, systems for therapeutic drug monitoring (TDM) have remained bulky and highly expensive, mostly due to the need for exceptionally precise, rapid, and highly accurate real-time on-site measurements. This dissertation focuses on the design, development, and implementation of miniaturized PoC devices for achieving high sensitivity, selectivity, and reliability through a combination of hardware and software strategies at the edge. The first part of the dissertation introduces the design of single and multi-channel electrochemical readout platforms with a high voltage range, fast scan rates, and with nano-ampere resolution, covering a broad range of electrochemical excitation techniques. These platforms were paired with electrochemical-based sensors to detect SARS‑CoV‑2, bisphenol A, and ascorbic acid. The low power feature of the proposed platforms is demonstrated by powering the complete detection system with energy harvested from natural and artificial ambient light. The second part of the dissertation introduces the design and development of a miniaturized wearable device with a pico-ampere resolution, high-speed electrochemical frequency interface, and highly stable sensing circuitry. A complete in-vivo system is demonstrated for long-term (>4 hours) measurement, wherein molecules are detected and monitored directly from a probe inserted in the subcutaneous abdomen region of a Sprague-Dawley rat. A solution for sensor drift due to biofouling and interference is demonstrated thought to the integration with real-time processing software. Furthermore, integrating the aforementioned platforms with highly reduced dense neural network models is demonstrated to increase the robustness of the sensors, allowing the detection of contaminants in complex samples, improving the sensor selectivity, and providing timely diagnoses in-situ.
    • Investigating the phase separation of recombinant Heterochromatin Proteins 1 (HP1) of Caenorhabditis elegans

      Alotaibi, Aljoharah (2023-08-09) [Thesis]
      Advisor: Fischle, Wolfgang
      Committee members: Arold, Stefan T.; Aranda, Manuel
      The proper packaging of the genome in eukaryotic nuclei is essential for proper gene expression and cell function. Chromatin at the large scale is divided into two major compartments heterochromatin and euchromatin. Heterochromatin compromises the transcriptionally inactive tightly packaged regions of chromatin, while euchromatin is the transcriptionally active region of chromatin. The Heterochromatin Protein family (HP1) proteins are epigenetic hallmarks of constitutive heterochromatin. Recent evidence suggests human HP1α undergoes liquid-liquid phase separation suggesting a role for HP1 phase separation in the formation of compacted heterochromatin within HP1 droplets. Phase separation is a biophysical property of proteins with intrinsically disordered domains which are protein domains that lack a defined secondary structure and have the ability to undertake multiple conformations. In this thesis, I investigated the ability of C. elegans HP1 homologs HPL-2A and HPL-1 to phase separate utilizing directed mutations to elucidate the intermolecular interactions that govern this phenomenon and different assays to assess their phase separation. I concluded that HPL-2A is a bona fide phase separating protein that selectively condenses chromatin. HPL-2A’s phase separation depends on specific interactions, mainly dimerization and the presence of lysine and arginine residues in the hinge region. HPL-2A has a specific IDR that drives its phase separation which is the hinge region as the CTE and NTE are not essential for its phase separation.
    • The Optical Properties of Organic Photovoltaic PM6:Y6 Thin Films for Solar Cell Applications

      Dahman, Amr (2023-08-05) [Thesis]
      Advisor: Laquai, Frédéric
      Committee members: Fatayer, Shadi P.; Baran, Derya
      As Organic solar cells (OSCs) become a promising complementary to traditional inorganic solar cells, studying the optical properties of OSCs plays a critical role to understand and improve the performance of organic solar cells. Studying optical properties is essential because it can help to understand how light interacts with the materials used in organic solar cells, which can help to improve the efficiency of organic solar cells. In this work, the optical properties of the organic photovoltaic system PM6:Y6 prepared from two different solvents, namely, chloroform and o-xylene, were investigated. The optical constants, specifically the refractive index and absorption coefficient of thin films of these materials, and the effects of thermal annealing on the optical properties were studied. The optical properties of isotropic and anisotropic organic materials were also compared, and the obtained optical constants were used to simulate the optical properties of the devices using the transfer matrix approach. The results suggest that more accurate measurements and analysis of the optical constants help to achieve more accurate simulations. This, in turn, provides more information about how the molecular orientation affects the optical properties of OSCs. However, it is important to note that the optical properties of PM6:Y6 blends that were studied are limited to those obtained under the conditions used to prepare the films. In fact, changes in the thickness or concentrations of solutions will need to be considered as well. Lastly, the glass transition temperature was determined using the change in the ellipsometric data (Ψ). This helps to select and test different thermal annealing temperatures for the material system, which could improve the efficiency of the respective solar cells.
    • Cybersecure and Resilient Power Systems with Distributed Energy Resources

      Zografopoulos, Ioannis (2023-08) [Dissertation]
      Advisor: Konstantinou, Charalambos
      Committee members: Ahmed, Shehab; Canini, Marco; Lakshminarayana, Subhash
      Power systems constitute a pillar of the critical infrastructure and, as a result, their cybersecurity is paramount. Traditional power system architectures are moving from their original centralized nature to a distributed paradigm. This transition has been propelled by the rapid penetration of distributed energy resources (DERs) such as rooftop solar panels, battery storage, etc. However, with the introduction of new DER devices, technologies, and operation models, the threat surface of power systems is inadvertently expanding. This dissertation provides a comprehensive overview of the cybersecurity landscape of DER-enabled power systems outlining potential attack entry points, system vulnerabilities, and the corresponding cyberattack impacts. Cyber-physical energy systems (CPES) testbeds are crucial tools to study power systems and perform vulnerability analyses, test security defenses, and evaluate the impact of cyberattacks in a controlled manner without impacting the actual electric grid. This work also attempts to provide bottom-up security solutions to secure power systems from their lowest abstraction layer, i.e., hardware. Specifically, custom-built hardware performance counters (HPCs) are proposed for the detection of malicious firmware, e.g., malware, within DER inverter controllers. The experimental results prove that HPCs are an effective host-based defense and can accurately identify malicious firmware with minimum performance overheads. Also, methodologies to secure communication protocols and ensure the nominal operation of DER devices using physics-informed schemes are presented. First, DERauth, a battery-based secure authentication primitive that can be used to enhance the security of DER communication, is proposed and evaluated in a CPES testbed. Then, a physics-based attack detection scheme that leverages system measurements to construct models of autonomous DER agents is presented. These measurement-based models are then used to discern between nominal and malicious DER behavior. The dissertation concludes by discussing how the proposed defense mechanisms can be used synergistically in an automated framework for grid islanding to improve power system security and resilience, before it provides prospective directions for future research.
    • Experimental Study on the Influence of Ammonia and Hydrogen addition on Soot Formation in Laminar Coflow Ethylene Diffusion Flames

      Aydin, Faruk Yigit (2023-08) [Thesis]
      Advisor: Roberts, William L.
      Committee members: Lacoste, Deanna; Castaño, Pedro
      Ammonia and hydrogen are two alternative fuels that can help decarbonization as they can be produced using renewable energy. Ammonia has transportation, handling, and storage advantages over hydrogen even though its combustion characteristics are worse. One intermediate strategy to use ammonia or hydrogen as a fuel is to co-fire it with hydrocarbons. However, co-firing with hydrocarbons may emit harmful pollutants such as NOx and soot. This study investigates the effects of ammonia and hydrogen addition on soot formation in laminar coflow nitrogen-diluted-ethylene normal diffusion flames using experimental techniques. Ammonia and hydrogen were added separately to the fuel flow. Flame conditions from 0 to 50 vol% of the added species (ammonia or hydrogen) were tested. Laser diagnostics for measuring the distributions of polycyclic aromatic hydrocarbons (PAHs) and soot volume fraction (SVF), and intrusive measurements (using a thermocouple and probe sampling) were performed. Based on the results, ammonia addition suppressed soot formation while hydrogen addition enhanced it. In conditions with ammonia addition, the temperature measurements with a Type S thermocouple and adiabatic flame temperature simulations using CHEMKIN PRO showed similar temperature profiles and negligible adiabatic flame temperature differences respectively. The qualitative PAH measurements using planar laser induced fluorescence (PLIF) showed that the concentration of PAHs of four or larger rings reduced with ammonia addition. Soot volume fraction (SVF) measurements using planar laser induced incandescence (PLII) showed that the peak SVF decreased exponentially with ammonia addition. Particle size distributions showed that the incipient particles were formed, however growth to mature primary particles was limited with 25% or higher ammonia addition in the flame. Based on similar temperature profiles and decreasing trends in the distribution of PAHs and SVF, soot suppression with ammonia addition was linked to chemical effects. PLIF measurements with hydrogen addition could be affected by the temperature difference between the flames, therefore further investigation is needed. PLII measurements, however, showed that the soot volume fraction increased linearly with hydrogen addition.
    • High-entropy Alloying of Sn$^{2+}$ and Ge$^{2+}$ at the B-site of CsPbI$_3$ for Stable and Efficient Perovskite Solar Cells

      Khan, Mohammed (2023-08) [Thesis]
      Advisor: Schwingenschlögl, Udo
      Committee members: Elatab, Nazek; Laquai, Frédéric
      While the field of solar energy conversion has witnessed an impressive rise of perovskite photovoltaics, their commercial deployment is hampered by the the toxicity of lead and stability issues. We employ density functional theory to explore the potential of Ge$^{2+}$ and Sn$^{2+}$ as dopants at the B-site of the CsPbI$_{3}$ perovskite. The primary objective is to reduce the toxicity and improve the stability while retaining the optical absorption properties. All doped materials remained within the stability regions of the octahedral and tolerance factor parameters. They have direct bandgaps at the $\Gamma$ point with values spanning from 1.16 to 1.83 eV using HSE06 functional, as compared to 2.16 eV in the case of CsPbI$_3$. This reduction of the bandgap and the consequent red-shift of the absorption spectrum, particularly for Sn-rich materials, enables more effective photon absorption at low energy. Efficiency calculations reveal that all doped materials outperform pristine CsPbI$_{3}$, achieving an efficiency of 33.4$\%$ using the SLME method. Consequently, our findings underscore the promise of Ge and Sn doping of CsPbI$_{3}$ for the creation of lead-reduced, efficient, and more stable perovskite solar cells.
    • Tackling the Communication Bottlenecks of Distributed Deep Learning Training Workloads

      Ho, Chen-Yu (2023-08) [Dissertation]
      Advisor: Canini, Marco
      Committee members: Keyes, David E.; Fahmy, Suhaib A.; Park, KyoungSoo
      Deep Neural Networks (DNNs) find widespread applications across various domains, including computer vision, recommendation systems, and natural language processing. Despite their versatility, training DNNs can be a time-consuming process, and accommodating large models and datasets on a single machine is often impractical. To tackle these challenges, distributed deep learning (DDL) training workloads have gained increasing significance. However, DDL training introduces synchronization requirements among nodes, and the mini-batch stochastic gradient descent algorithm heavily burdens network connections. This dissertation proposes, analyzes, and evaluates three solutions addressing the communication bottleneck in DDL learning workloads. The first solution, SwitchML, introduces an in-network aggregation (INA) primitive that accelerates DDL workloads. By aggregating model updates from multiple workers within the network, SwitchML reduces the volume of exchanged data. This approach, which incorporates switch processing, end-host protocols, and Deep Learning frameworks, enhances training speed by up to 5.5 times for real-world benchmark models. The second solution, OmniReduce, is an efficient streaming aggregation system designed for sparse collective communication. It optimizes performance for parallel computing applications, such as distributed training of large-scale recommendation systems and natural language processing models. OmniReduce achieves maximum effective bandwidth utilization by transmitting only nonzero data blocks and leveraging fine-grained parallelization and pipelining. Compared to state-of-the-art TCP/IP and RDMA network solutions, OmniReduce outperforms them by 3.5 to 16 times, delivering significantly better performance for network-bottlenecked DNNs, even at 100 Gbps. The third solution, CoInNetFlow, addresses congestion in shared data centers, where multiple DNN training jobs compete for bandwidth on the same node. The study explores the feasibility of coflow scheduling methods in hierarchical and multi-tenant in-network aggregation communication patterns. CoInNetFlow presents an innovative utilization of the Sincronia priority assignment algorithm. Through packet-level DDL job simulation, the research demonstrates that appropriate weighting functions, transport layer priority scheduling, and gradient compression on low-priority tensors can significantly improve the median Job Completion Time Inflation by over $70\%$. Collectively, this dissertation contributes to mitigating the network communication bottleneck in distributed deep learning. The proposed solutions can enhance the efficiency and speed of distributed deep learning systems, ultimately improving the performance of DNN training across various domains.
    • Simulating the Use of Hydrogen Peroxide in Diesel Autothermal Reforming: A Comparative Study

      Alhussain, Ali S. (2023-08) [Thesis]
      Advisor: Dally, Bassam
      Committee members: Grande, Carlos A.; Sarathy, Mani
      This thesis reports the outcome of a simulation study that examines the feasibility of using hydrogen peroxide as an alternative oxidant in the autothermal reforming (ATR) of diesel. The primary objective is to compare hydrogen peroxide's performance against conventional oxidants in reforming, focusing on product distribution and three pivotal process properties: diesel conversion, hydrogen production, and ethylene generation. The study further investigates the influence of the heat of decomposition on the performance and reaction routes of different oxidants. Additionally, a comparative analysis is conducted on the reforming performance in different reformer configurations, specifically contrasting a combined-reformer-configuration with a catalytic-reformer configuration. The ANSYS Chemkin-Pro is utilized to understand the potential benefits and challenges of the proposed approached. A reduced chemical mechanism of N-heptane/Toluene reforming as a surrogate for diesel, combined with a detailed surface reaction mechanism of propene on a three-way Pt/Rh catalyst are used in this study. It is found that the use of hydrogen peroxide as an oxidant demonstrated a complete fuel conversion and 183% higher hydrogen yield when compared with conventional oxidants. It also led to a 12% lower generation of ethylene, a precursor for coke formation. The catalytic-reformer configuration showed superior performance over the combined-reformer-configuration in terms of hydrogen yield. The insights from this study offer valuable perspectives on the feasibility and efficiency of using hydrogen peroxide as an alternative oxidant in the ATR of diesel, paving the way for potential advancements in the field.