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  • Machine Learning Models for Biomedical Ontology Integration and Analysis

    Smaili, Fatima Z. (2020-09-13) [Dissertation]
    Advisor: Gao, Xin
    Committee members: Rzhetsky, Andrey; Hoehndorf, Robert; Arold, Stefan T.
    Biological knowledge is widely represented in the form of ontologies and ontologybased annotations. Biomedical ontologies describe known phenomena in biology using formal axioms, and the annotations associate an entity (e.g. genes, diseases, chemicals, etc.) with a set of biological concepts. In addition to formally structured axioms, ontologies contain meta-data in the form of annotation properties expressed mostly in natural language which provide valuable pieces of information that characterize ontology concepts. The structure and information contained in ontologies and their annotations make them valuable for use in machine learning, data analysis and knowledge extraction tasks. I develop the rst approaches that can exploit all of the information encoded in ontologies, both formal and informal, to learn feature embeddings of biological concepts and biological entities based on their annotations to ontologies. Notably, I develop the rst approach to use all the formal content of ontologies in the form of logical axioms and entity annotations to generate feature vectors of biological entities using neural language models. I extend the proposed algorithm by enriching the obtained feature vectors through representing the natural language annotation properties within the ontology meta-data as axioms. Transfer learning is then applied to learn from the biomedical literature and apply on the formal knowledge of ontologies. To optimize learning that combines the formal content of biomedical ontologies and natural language data such as the literature, I also propose a new approach that uses self-normalization with a deep Siamese neural network that improves learning from both the formal knowledge within ontologies and textual data. I validate the proposed algorithms by applying them to the Gene Ontology to generate feature vectors of proteins based on their functions, and to the PhenomeNet ontology to generate features of genes and diseases based on the phenotypes they are associated with. The generated features are then used to train a variety of machinelearning based classi ers to perform di erent prediction tasks including the prediction of protein interactions, gene{disease associations and the toxicological e ects of chemicals. I also use the proposed methods to conduct the rst quantitative evaluation of the quality of the axioms and meta-data included in ontologies to prove that including axioms as background improves ontology-based prediction. The proposed approaches can be applied to a wide range of other bioinformatics research problems including similarity-based prediction and classi cation of interaction types using supervised learning, or clustering.
  • Induction of Salt Tolerance by Enterobacter sp. SA187 in the Model Organism Arabidopsis thaliana

    Alzubaidy, Hanin S. (2020-09) [Dissertation]
    Advisor: Hirt, Heribert
    Committee members: Blilou, Ikram; Aranda, Manuel; deZelicourt, Axel; Krasensky-Wrzaczek, Julia
    Arid and semi-arid regions, mostly found in developing countries with exponentially increasing populations, are in chronic lack of water thereby severely limiting agricultural production. Irrigation with saline water, which is available in large quantities, could be an obvious solution, but current crops are all salt sensitive. Although major efforts are underway to breed salt tolerant crops, no breakthrough results have yet been obtained. One alternative could rely on plant-interacting microbiota communities. Indeed, rhizophere and endosphere microbial communities are distinct from those of the surrounding soils, and these specific communities contribute to plant growth and health by increasing nutrient availability or plant resistance towards abiotic and biotic stresses. Here we show that plant microbe interactions induce plant tolerance to multiple stresses. From a collection of strains isolated from the desert plant Indigofera argentea, we could identify at least four different strategies to induce salt stress tolerance in Arabidopsis thaliana. A deep analysis of Enterobacter sp. SA187 showed that it induces Arabidopsis tolerance to salinity through activation of the ethylene signaling pathway. Interestingly, although SA187 does not produce ethylene as such, the association of SA187 with plants induces the expression of the methionine salvage pathway in SA187 resulting in the conversion of bacterially produced 2-keto-4-methylthiobutyric acid (KMBA) to ethylene. In addition, a metabolic network characterization of both SA187 and Arabidopsis in their free-living and endophytic state revealed that the sulfur metabolic pathways are strongly upregulated in both organisms. Furthermore, plant genetic experiments verified the essential role of the sulfur metabolism and ethylene signaling in plant salt stress tolerance. Our findings demonstrate how successful plant microbes of a given community can help other plants to enhance tolerance to abiotic stress, and reveal a part of the complex molecular communication process during beneficial plant-microbe interaction.
  • Indoor 3D Scene Understanding Using Depth Sensors

    Lahoud, Jean (2020-09) [Dissertation]
    Advisor: Ghanem, Bernard
    Committee members: Heidrich, Wolfgang; Wonka, Peter; Cremers, Daniel
    One of the main goals in computer vision is to achieve a human-like understand- ing of images. Nevertheless, image understanding has been mainly studied in the 2D image frame, so more information is needed to relate them to the 3D world. With the emergence of 3D sensors (e.g. the Microsoft Kinect), which provide depth along with color information, the task of propagating 2D knowledge into 3D becomes more attainable and enables interaction between a machine (e.g. robot) and its environ- ment. This dissertation focuses on three aspects of indoor 3D scene understanding: (1) 2D-driven 3D object detection for single frame scenes with inherent 2D informa- tion, (2) 3D object instance segmentation for 3D reconstructed scenes, and (3) using room and floor orientation for automatic labeling of indoor scenes that could be used for self-supervised object segmentation. These methods allow capturing of physical extents of 3D objects, such as their sizes and actual locations within a scene.
  • A Game-theoretic Implementation of the Aerial Coverage Problem

    Alghamdi, Anwaar (2020-09) [Thesis]
    Advisor: Shamma, Jeff S.
    Committee members: Laleg-Kirati, Taous-Meriem; Elhoseiny, Mohamed H.
    Game theory can work as a coordination mechanism in multi-agent robotic systems by representing each robot as a player in a game. In ideal scenarios, game theory algorithms guarantee convergence to optimal configurations and have been widely studied for many applications. However, most of the studies focus on theoretical analysis and lack the details of complete demonstrations. In this regard, we implemented a real-time multi-robot system in order to investigate how game-theoretic methods perform in non-idealized settings. An aerial coverage problem was modeled as a potential game, where each aerial vehicle is an independent decision-making player. These players take actions under limited communication, and each is equipped with onboard vision capabilities. Three game-theoretic methods have been modified and implemented to solve this problem. All computations are performed using onboard devices, independent of any ground entity. The performance of the system is analyzed and compared with different tests and configurations
  • High-Speed GaN-Based Distributed-Feedback Lasers and Optoelectronics

    Holguin Lerma, Jorge Alberto (2020-09) [Thesis]
    Advisor: Ooi, Boon S.
    Committee members: Ohkawa, Kazuhiro; Baran, Derya; Kuo, Hao-Chung
    Gallium nitride (GaN) is a semiconductor material highly regarded for visible light generation since it provides the most efficient platform for compact violet, blue, and green light emitters, and in turn, high-quality and ubiquitous white lighting. Despite this fact, the potential of the GaN platform has not been fully exploited. This potential must enable the precise control in the various properties of light, realizing functions beyond the conventional. Simultaneously, the field of the telecommunications is looking for candidate technologies fit for wireless transmission in the next generations of communication. Visible light communication (VLC) may play a significant role in the future of the last mile of the network by providing both a fast internet connection and a high-quality illumination. Hence, a variety of optoelectronic platforms, including distributed-feedback (DFB) lasers, superluminescent diodes (SLDs), and multi-section lasers, can be used to exploit the full potential of GaN while offering unprecedented solutions for VLC and other applications, such as atomic clocks, high-resolution fluorescence microscopy, and on-chip nonlinear processing at visible wavelengths. This dissertation demonstrates green and sky-blue DFB lasers based on GaN, with resolution-limited single-mode emission at wavelengths around 514 nm and 480 nm, side-mode suppression ratio as large as 42.4 dB, and application to up to 10.5 Gbit/s data transmission. Preliminary observations of DFB lasers with emission close to the Fraunhofer lines are presented, offering a pathway for low-background noise applications. Blue-emitting SLDs are used to demonstrate a 3.8 Gbit/s transmitter while achieving spectral efficiency of up 118.2 (mW・nm)/(kA/cm2) in continuous-wave operation. Visual quality is confirmed by coherence length and white light generation. Short-wavelength SLDs have the potential for higher resolution and fluorescence excitation in classical optical coherence tomography and fiber gyroscopes. The demonstration of a two-section green laser diode is presented, achieving coupled-cavity lasing at wavelengths of 514 nm based on an integrated green laser–absorber in self-colliding pulse configuration, operated in continuous-wave electrical injection. The integrated laser offer potential for mode- locked and Q-switched lasing. The integrated laser is suitable for reconfiguration where laser–modulator, laser–absorber, and laser–amplifier are proposed and investigated at green wavelengths.
  • The Umklapp Scattering and Spin Mixing Conductance in Collinear Antiferromagnets

    Alshehri, Nisreen (2020-08-31) [Thesis]
    Advisor: Manchon, Aurelien
    Committee members: Schwingenschlögl, Udo; Wu, Ying
    Antiferromagnetic spintronics is a new promising field in applied magnetism. Antiferromagnetic materials display a staggered arrangement of magnetic moments so that they exhibit no overall magnetization while possessing a local magnetic order. Unlike ferromagnets that possess a homogeneous magnetic order, the spin-dependent phenomena occur locally upon the interaction between the itinerant electron and the localized magnetic moments. In fact, unique spin transport properties such as anisotropic magnetoresistance, anomalous Hall effect, magnetooptical Kerr effect, spin transfer torque and spin pumping have been predicted and observed, proving that antiferromagnetic materials stand out as promising candidates for spin information control and manipulation, and could potentially replace ferromagnets as the active part of spintronic devices. As a matter of fact, owing to their vanishing net magnetization, they produce no parasite stray fields, hence, they are mostly insensitive to external magnetic fields perturbations and displaying ultrafast magnetic dynamics. When a spin current is sent into an antiferromagnet, it experiences spin-dependent scattering, a mechanism that controls the spin transfer torque as well as the spin transmission across the antiferromagnet. The fully compensated antiferromagnetic interfaces are full of intriguing properties. For example, itinerant electron impinging on such an interface experiences a spin-flip associated with the sub-lattices interchange. This process, associated with Umklapp scattering, gives rise to a non-vanishing spin mixing conductance that governs spin transfer torque, spin pumping, and spin transmission. The thesis explores the mechanism of Umklapp scattering at a staggered antiferromagnetic interface and its associated spin mixing conductance. In this project we consider two systems of bilayer and trilayer antiferromagnetic (L-type, G-type) heterostructures. We first study the scattering coeffcients at the interface implemented by adopting the tight-binding model and proper boundary conditions. Then, in the trilayer case, we study the spin mixing conductance and the dephasing length associated with the transition from ferromagnetic order to antiferromagnetic order.
  • Trajectory Planning for Autonomous Underwater Vehicles: A Stochastic Optimization Approach

    Albarakati, Sultan (2020-08-30) [Dissertation]
    Advisors: Knio, Omar; Shamma, Jeff S.
    Committee members: Hoteit, Ibrahim; Lermusiaux, Pierre F.J.
    In this dissertation, we develop a new framework for 3D trajectory planning of Autonomous Underwater Vehicles (AUVs) in realistic ocean scenarios. The work is divided into three parts. In the rst part, we provide a new approach for deterministic trajectory planning in steady current, described using Ocean General Circulation Model (OGCM) data. We apply a Non-Linear Programming (NLP) to the optimal time trajectory planning problem. To demonstrate the effectivity of the resulting model, we consider the optimal time trajectory planning of an AUV operating in the Red Sea and the Gulf of Aden. In the second part, we generalize our 3D trajectory planning framework to time-dependent ocean currents. We also extend the framework to accommodate multi-objective criteria, focusing speci cally on the Pareto front curve between time and energy. To assess the effectiveness of the extended framework, we initially test the methodology in idealized settings. The scheme is then demonstrated for time-energy trajectory planning problems in the Gulf of Aden. In the last part, we account for uncertainty in the ocean current eld, is described by an ensemble of flow realizations. The proposed approach is based on a non-linear stochastic programming methodology that uses a risk-aware objective function, accounting for the full variability of the flow ensemble. We formulate stochastic problems that aim to minimize a risk measure of the travel time or energy consumption, using a fexible methodology that enables the user to explore various objectives, ranging seamlessly from risk-neutral to risk-averse. The capabilities of the approach are demonstrated using steady and transient currents. Advanced visualization tools have been further designed to simulate results.
  • Fundamental Molecular Communication Modelling

    Briantceva, Nadezhda (2020-08-25) [Thesis]
    Advisor: Alouini, Mohamed-Slim
    Committee members: Keyes, David E.; Parsani, Matteo
    As traditional communication technology we use in our day-to-day life reaches its limitations, the international community searches for new methods to communicate information. One such novel approach is the so-called molecular communication system. During the last few decades, molecular communication systems become more and more popular. The main di erence between traditional communication and molecular communication systems is that in the latter, information transfer occurs through chemical means, most often between microorganisms. This process already happens all around us naturally, for example, in the human body. Even though the molecular communication topic is attractive to researchers, and a lot of theoretical results are available - one cannot claim the same about the practical use of molecular communication. As for experimental results, a few studies have been done on the macroscale, but investigations at the micro- and nanoscale ranges are still lacking because they are a challenging task. In this work, a self-contained introduction of the underlying theory of molecular communication is provided, which includes knowledge from di erent areas such as biology, chemistry, communication theory, and applied mathematics. Two numerical methods are implemented for three well-studied partial di erential equations of the MC eld where advection, di usion, and the reaction are taken into account. Numerical results for test cases in one and three dimensions are presented and discussed in detail. Conclusions and essential analytical and numerical future directions are then drawn.
  • Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters

    Hanzely, Filip (2020-08-20) [Dissertation]
    Advisor: Richtarik, Peter
    Committee members: Tempone, Raul; Ghanem, Bernard; Wright, Stephen; Zhang, Tong
    Many key problems in machine learning and data science are routinely modeled as optimization problems and solved via optimization algorithms. With the increase of the volume of data and the size and complexity of the statistical models used to formulate these often ill-conditioned optimization tasks, there is a need for new e cient algorithms able to cope with these challenges. In this thesis, we deal with each of these sources of di culty in a di erent way. To e ciently address the big data issue, we develop new methods which in each iteration examine a small random subset of the training data only. To handle the big model issue, we develop methods which in each iteration update a random subset of the model parameters only. Finally, to deal with ill-conditioned problems, we devise methods that incorporate either higher-order information or Nesterov's acceleration/momentum. In all cases, randomness is viewed as a powerful algorithmic tool that we tune, both in theory and in experiments, to achieve the best results. Our algorithms have their primary application in training supervised machine learning models via regularized empirical risk minimization, which is the dominant paradigm for training such models. However, due to their generality, our methods can be applied in many other elds, including but not limited to data science, engineering, scienti c computing, and statistics.
  • Halide Perovskites: Materials Properties and Emerging Applications

    Haque, Mohammed (2020-08-11) [Dissertation]
    Advisor: Baran, Derya
    Committee members: Alshareef, Husam N.; Mohammed, Omar F.; Saliba, Michael
    Semiconducting materials have emerged as the cornerstone of modern electronics owing to their extensive device applications. There is a continuous quest to find cost-effective and low-temperature compatible materials for future electronics. The recent reemergence of solution processable halide perovskites have taken the optoelectronics research to new paradigms. Apart from photovoltaics, the versatile characteristics of halide perovskites have resulted in a multitude of applications. This dissertation focuses on various properties and emerging applications particularly, photodetection and thermoelectrics of both hybrid and all-inorganic halide perovskites. It is important to understand the underlying properties of perovskites to further develop this class of materials. One of the major hurdles restricting the practical devices of perovskites is their sensitivity to moisture. A systematic investigation on the effect of humidity on hybrid perovskites revealed different degree of moisture uptake behaviour for micropatterns, films, and single crystals. Degradation pathways and processing limitations of hybrid perovskites are discussed which will aid in designing strategies to overcome these impediments for future large scale device integration. There is a recent surge of reports on doping hybrid perovskites to control its optoelectronic properties but in-depth understanding of these dopants and their ramifications remain unexplored. The effect of doping on the optoelectronic properties of hybrid perovskites is studied and a model is proposed for the observed behavior. Leveraging on the rapid growth of microcrystalline perovskite films, for the first time tunable bifacial perovskite photodetectors were fabricated, operating in both broadband and narrowband regimes. Furthermore, self-biased single crystalline photodetectors based on all-inorganic perovskite were developed with high on-off ratio and low dark current. Halide perovskites are emerging as a new class of materials for thermoelectric applications owing to their ultralow thermal conductivity and decent Seebeck coefficient. Here, halide perovskites are evaluated in terms of composition, stability, and performance tunability to understand their thermoelectric efficacy. Finally, as an alternative to Pb and Sn-based perovskites, a new hybrid was discovered with ultralow thermal conductivity and a general synthetic route to design such hybrids is proposed.
  • Sustainable Approaches to Reduce Biofouling and Biocorrosion in Seawater and Wastewater Environment

    Scarascia, Giantommaso (2020-08) [Dissertation]
    Advisor: Hong, Pei-Ying
    Committee members: Pain, Arnab; Saikaly, Pascal; Suarez, Laura Machuca
    Biofouling and biocorrosion are due to unwanted deposition of microorganisms on surfaces that are exposed to different types of water. This dissertation focuses on the application of innovative strategies to inhibit biofouling and biocorrosion. Specifically, the strategies examined in this dissertation, namely the use of bacteriophages and quorum quenchers, aim to minimize reliance on the conventional chemical cleaning agents and to reduce chemical-induced hazards on health, safety and environment. First, we analyzed the use of bacteriophages to remove biofoulants on ultrafiltration membrane used in seawater reverse osmosis pretreatment. Our findings revealed that bacteriophages were able to remain active against membrane-associated Pseudomonas aeruginosa at a broad range of temperature, pH and salinity. Bacteriophages were also shown to inhibit biofilm and to reduce transmembrane pressure increment, when applied alone or in combination with chemical agents. Second, this dissertation explores the use of quorum quenchers to inhibit biocorrosion in seawater environment. To do so, we first examined for the presence of quorum sensing system in sulfate reducing bacteria (SRB). Through transcriptomic analysis, we further demonstrate a strong correlation between quorum sensing, biofilm formation and biocorrosion. Therefore, the use of quorum sensing inhibitors was suggested to prevent biofilm formation and biocorrosion caused by SRB in seawater. Through findings from Chapter 2 and 3, we introduced the use of alternative biocidal agents to tackle biofouling and biocorrosion. Compared to quorum quenchers, bacteriophages showed better antibiofilm potential and easier applicability at larger scale. However, bacteriophages alone were insufficient to reduce biofilm formation as phage resistance was observed over long-term experiments. Hence in the last chapter, we further explored the use of bacteriophages to alleviate biofouling that occurred during wastewater treatment process, by combining their infection with UV irradiation. UV was used both for its biocidal effect and to trigger phage infection against bacteria. Our findings indicate that the combined treatment was able to remove mature biofoulants from the membrane. Overall, this dissertation demonstrates the use of bacteriophages and quorum quenchers against biofilm. These two approaches can serve to reduce the amount of chemicals used during cleaning, thus providing a more sustainable way of minimizing biofilm-associated problems.
  • Additively Manufactured Vanadium Dioxide (VO2) based Radio Frequency Switches and Reconfigurable Components

    Yang, Shuai (2020-08) [Dissertation]
    Advisor: Shamim, Atif
    Committee members: Fariborzi, Hossein; Anthopoulos, Thomas D.; Tentzeris, Manos M.
    In a wireless system, the frequency-reconfigurable RF components are highly desired because one such component can replace multiple RF components to reduce the size, cost, and weight. Typically, the reconfigurable RF components are realized using capacitive varactors, PIN diodes, or MEMS switches. Most of these RF switches are expensive, rigid, and need tedious soldering steps, which are not suitable for futuristic flexible and wearable applications. Therefore, there is a need to have a solution for low cost, flexible, and easy to integrate RF switches. All the above-mentioned issues can be alleviated if these switches can be simply printed at the place of interest. In this work, we have demonstrated vanadium dioxide (VO2) based RF switches that have been realized through additive manufacturing technologies (inkjet printing and screen printing), which dramatically brings the cost down to a few cents. Also, no soldering or additional attachment step is required as the switch can be simply printed on the RF component. The printed VO2 switches are configured in two types (shunt configuration and series configuration) where both types have been characterized with two activation mechanisms (thermal activation and electrical activation) up to 40 GHz. The measured insertion loss of 1-3 dB, isolation of 20-30 dB, and switching speed of 400 ns are comparable to other non-printed and expensive RF switches. As an application for the printed VO2 switches, a fully printed frequency reconfigurable filter has also been designed in this work. An open-ended dual-mode resonator with meandered loadings has been co-designed with the VO2 switches, resulting in a compact filter with decent insertion loss of 2.6 dB at both switchable frequency bands (4 GHz and 3.75 GHz). Moreover, the filter is flexible and highly immune to the bending effect, which is essential for wearable applications. Finally, a multi-parameter (switch thickness, width, length, temperature) model has been established using a customized artificial neural network (ANN) to achieve a faster simulation speed. The optimized model’s average error and correlation coefficient are only 0.0003 and 0.9905, respectively, which both indicate the model’s high accuracy.
  • Shale Reservoir Simulation in Basins with High Pore Pressure and Small Differential Stress

    Arias, Daniela (2020-08) [Thesis]
    Advisor: Patzek, Tadeusz
    Committee members: Hoteit, Hussein; Finkbeiner, Thomas; Klimkowski, Lukasz
    Hydrocarbon production from mudrock (“shale”) reservoirs is fundamental in the global energy supply. Extracting commercial amounts of hydrocarbons from shale plays requires a combination of horizontal well drilling, hydraulic fracturing, and multi-stage completions. This technology creates conductive hydrofractures that may interact with pre-existing natural fractures and bedding planes. Microseismic studies and field pilots have uncovered evidence of complex hydrofracture geometries that can lead to unsatisfactory wellbore flow performance. This study examines the effects of three hydrofracture geometries (”scenarios”) on wellbore production in overpressured shale oil reservoirs using a commercial reservoir simulator (CMG IMEX). The first scenario is our reference case. It comprises ideal ized and vertical hydrofractures. The second scenario has an orthogonal hydrofracture network made up of vertical hydrofractures with perpendicular secondary fractures. The third scenario has vertical hydrofractures with horizontal bedding plane frac tures. We generated additional simulation models that aim to capture the effect on hydrocarbon production of different fracture properties, such as natural fracture ori entation and spacing, number of hydrofractures per stage, number of perpendicular secondary fractures and horizontal fractures, and fracture closure mechanism. The results show that ideal planar fractures are an oversimplification of the hydrofracture geometry in anisotropic shale plays. They fail to represent the complex geometry in reservoir simulation and lead to unexpected hydrocarbon production forecasting. They also show that the generation of unpropped horizontal fractures harms hydro carbon productivity, while perpendicular secondary fractures enhance initial reservoir 5 fluid production. The generation of horizontal hydrofractures is a particular scenario that may occur in reservoirs with high pore pressure and transitional strike-slip to reverse faulting regime. These conditions have been reported in unconventional source rock plays, like the Marcellus shale in northeast Pennsylvania and southwest Virginia, and the Tuwaiq Mountain formation in the Jafurah Basin in Saudi Arabia. Our findings reveal that the presence of horizontal hydrofractures might reduce the cumulative hydrocarbon production by 20%, and the initial hydrocarbon production by 55% compared to the reference case. Our work shows unique reservoir simulations that enable us to assess the impact of different variables on wellbore production performance and understand the effects of varied hydrofracture geometries on hydrocarbon production.
  • Broadband Reflective Metalens in Visible Band Based on Bragg Reflector Multilayers for VECSEL Applications

    Alnakhli, Zahrah J. (2020-08) [Thesis]
    Advisor: Li, Xiaohang
    Committee members: Roqan, Iman S.; Salama, Khaled N.
    In conventional optics, curved lenses focus light rays to a focal point after light passes through them. These lenses have been designed to shape the wavefront of the incident beam as it emerges from the curved surface of the lens. Conventional lenses suffer from many limitations, such as limited optical quality for imaging and integration difficulties with other optical components due to their large size, huge thickness, as well as being difficult to manufacture. Using subwavelength structure, it is possible to fabricate flat, thin lenses (metalenses) with new optical properties not found in nature, in which many fundamental properties of light (like polarization, focal point, and phase) can be controlled with high accuracy. This results in high resolution and high quality of optical imaging. This thesis demonstrates a new design of reflective metalens, in which the metalens structure is integrated with another optical component: Distributed Bragg Reflector (DBR). The metalens planer is a two-dimensional ultrathin planer arranged as an array with subwavelength separation distance. In recent works, a metalens was integrated with (metal/dielectric)-mirrors to form reflective metalenses. Simulation results show that, high-focusing efficiency is obtained for the lens (> 60%) with the ability to reflect96% of total incident optical power. In comparison, the new metalens-DBR design - processes maintain the same high-focusing efficiency, but with a reflectance of 99.99%, which makes it promising for optoelectronic integration and perfectly suitable for integration with Vertical Cavity Surface Emitting Lasers (VCSEL) technology. This study of the optical properties: focal length; optical aberration; insensitivity to light polarization; and focusing efficiency of demonstrated metalens was done mainly by Finite Difference Time Domaine (FDTD) by using Lumerical FDTD solution.
  • Halide Perovskite Single Crystals: Design, Growth, and Characterization

    Zhumekenov, Ayan A. (2020-08) [Dissertation]
    Advisor: Bakr, Osman
    Committee members: Mohammed, Omar F.; Alshareef, Husam N.; Stranks, Samuel D.
    Halide perovskites have recently emerged as the state-of-the-art semiconductors with the unique combination of outstanding optoelectronic properties and facile solution synthesis. Within only a decade of research, they have witnessed a remarkable success in photovoltaics and shown great potential for applications in light-emitting devices, photodetectors, and high-energy sensors. Yet, the majority of current perovskite-based devices still rely on polycrystalline thin films which, as will be discussed in Chapter 2, exhibit inferior charge transport characteristics and increased tendency to chemical degradation compared to their single-crystalline analogues. In this regard, unburdened from the effects of grain boundaries, single crystals demonstrate the upper limits of semiconductor performance. Their study is, thus, important from both fundamental and practical aspects, which present the major objectives of this dissertation. In Chapter 3, we study the intrinsic charge transport and recombination characteristics of single crystals of formamidinium lead halide perovskites. While, in Chapter 4, we investigate the mechanistic origins of rapid synthesis of halide perovskite single crystals by inverse temperature crystallization. Understanding the nucleation and growth mechanisms of halide perovskites enables us to design strategies toward integrating their single crystals into device applications. Namely, in Chapters 5 and 6, we demonstrate crystal engineering approaches for tailoring the thicknesses and facets of halide perovskite single crystals to make them suitable for, respectively, vertical and planar architecture optoelectronic devices. The findings of this dissertation are expected to benefit future studies on fundamental characterization of halide perovskites, as well as motivate researchers to develop perovskite-based optoelectronic devices with better crystallinity, performance and stability.
  • NonlinearWave Motion in Viscoelasticity and Free Surface Flows

    Ussembayev, Nail (2020-07-24) [Dissertation]
    Advisor: Markowich, Peter A.
    Committee members: Thoroddsen, Sigurdur T; Tzavaras, Athanasios; Bona, Jerry L.
    This dissertation revolves around various mathematical aspects of nonlinear wave motion in viscoelasticity and free surface flows. The introduction is devoted to the physical derivation of the stress-strain constitutive relations from the first principles of Newtonian mechanics and is accessible to a broad audience. This derivation is not necessary for the analysis carried out in the rest of the thesis, however, is very useful to connect the different-looking partial differential equations (PDEs) investigated in each subsequent chapter. In the second chapter we investigate a multi-dimensional scalar wave equation with memory for the motion of a viscoelastic material described by the most general linear constitutive law between the stress, strain and their rates of change. The model equation is rewritten as a system of first-order linear PDEs with relaxation and the well-posedness of the Cauchy problem is established. In the third chapter we consider the Euler equations describing the evolution of a perfect, incompressible, irrotational fluid with a free surface. We focus on the Hamiltonian description of surface waves and obtain a recursion relation which allows to expand the Hamiltonian in powers of wave steepness valid to arbitrary order and in any dimension. In the case of pure gravity waves in a two-dimensional flow there exists a symplectic coordinate transformation that eliminates all cubic terms and puts the Hamiltonian in a Birkhoff normal form up to order four due to the unexpected cancellation of the coefficients of all fourth order non-generic resonant terms. We explain how to obtain higher-order vanishing coefficients. Finally, using the properties of the expansion kernels we derive a set of nonlinear evolution equations for unidirectional gravity waves propagating on the surface of an ideal fluid of infinite depth and show that they admit an exact traveling wave solution expressed in terms of Lambert’s W-function. The only other known deep fluid surface waves are the Gerstner and Stokes waves, with the former being exact but rotational whereas the latter being approximate and irrotational. Our results yield a wave that is both exact and irrotational, however, unlike Gerstner and Stokes waves, it is complex-valued.
  • An Investigation of the Stresses Causing the Spontaneous Delamination of Titanium-Platinum Bilayers Leading to The Formation of Nanogaps

    AlBatati, Afnan (2020-07-23) [Thesis]
    Advisor: Anthopoulos, Thomas D.
    Committee members: Laquai, Frédéric; Lubineau, Gilles
    Adhesion lithography has been used to pattern nanogaps between two electrodes of the same or different metals onto a substrate. Patterning Al and Ti/Pt bilayer electrodes have been shown to form nanogaps leaving behind relatively consistent nanogaps of less than 12 nm between the electrodes. These nanogaps are formed without the need for adhesion lithography due to the bilayer spontaneously delaminating from the aluminum electrodes, In this study, the stresses in the Ti/Pt bilayer are investigated to determine the amount of stress required for delamination and the properties causing it. The goal is to recreate this stress mechanism in other patterned metals such as Au and Al. Heat cycling is used to induce high stress in other metal electrode combinations in an attempt to induce spontaneous delamination in Al and Au but fails up to 310°C annealing temperature. Theoretical methods are used to determine the stress: searching for an appropriate mathematical model and using finite element analysis in ABAQUS software to create a simulation of the delaminating Ti/Pt bilayer. The stress is found to be caused by the residual stresses in platinum and the high energy e-beam deposition method. An experimental value for the stress and the ability to recreate it in other metals remains elusive.
  • Hierarchical Approximation Methods for Option Pricing and Stochastic Reaction Networks

    Ben Hammouda, Chiheb (2020-07-22) [Dissertation]
    Advisor: Tempone, Raul
    Committee members: Gomes, Diogo A.; Jasra, Ajay; Gobet, Emmanuel; Kebaier, Ahmed
    In biochemically reactive systems with small copy numbers of one or more reactant molecules, stochastic e ects dominate the dynamics. In the rst part of this thesis, we design novel e cient simulation techniques for a reliable and fast estimation of various statistical quantities for stochastic biological and chemical systems under the framework of Stochastic Reaction Networks. In the rst work, we propose a novel hybrid multilevel Monte Carlo (MLMC) estimator, for systems characterized by having simultaneously fast and slow timescales. Our hybrid multilevel estimator uses a novel split-step implicit tau-leap scheme at the coarse levels, where the explicit tau-leap method is not applicable due to numerical instability issues. In a second work, we address another challenge present in this context called the high kurtosis phenomenon, observed at the deep levels of the MLMC estimator. We propose a novel approach that combines the MLMC method with a pathwise-dependent importance sampling technique for simulating the coupled paths. Our theoretical estimates and numerical analysis show that our method improves the robustness and complexity of the multilevel estimator, with a negligible additional cost. In the second part of this thesis, we design novel methods for pricing nancial derivatives. Option pricing is usually challenging due to: 1) The high dimensionality of the input space, and 2) The low regularity of the integrand on the input parameters. We address these challenges by developing di erent techniques for smoothing the integrand to uncover the available regularity. Then, we approximate the resulting integrals using hierarchical quadrature methods combined with Brownian bridge construction and Richardson extrapolation. In the rst work, we apply our approach to e ciently price options under the rough Bergomi model. This model exhibits several numerical and theoretical challenges, implying classical numerical methods for pricing being either inapplicable or computationally expensive. In a second work, we design a numerical smoothing technique for cases where analytic smoothing is impossible. Our analysis shows that adaptive sparse grids' quadrature combined with numerical smoothing outperforms the Monte Carlo approach. Furthermore, our numerical smoothing improves the robustness and the complexity of the MLMC estimator, particularly when estimating density functions.
  • Stochastic Geometry-based Analysis of LEO Satellite Communication Systems

    Talgat, Anna (2020-07-21) [Thesis]
    Advisor: Alouini, Mohamed-Slim
    Committee members: Gomes, Diogo A.; Park,Ki-Hong; Kishk, Mustafa Abdelsalam
    Wireless coverage becomes one of the most signi cant needs of modern society because of its importance in various applications such as health, distance educa- tion, industry, and much more. Therefore, it is essential to provide wireless coverage worldwide, including remote areas, rural areas, and poorly served locations. Recent advances in Low Earth Orbit (LEO) satellite communications provide a promising solution to address these issues in poorly served locations. The thesis studies the performance of a multi-level LEO satellite communication system. More precisely, we model the LEO satellites' location as Binomial Point Process (BPP) on a spherical surface at n di erent altitudes given that the number of satellites at each altitude ak is Nk where 1 k n and study the distance distribution. The distance distribution is characterized in two categories depending on the location of the observation point: contact distance and the nearest neighbor distance. For that proposed model, we study the user coverage probability by using tools from stochastic geometry for a scenario where satellite earth stations (ESs) with two antennas are deployed on the ground where one of the antennas communicates with the user while the other communicates with LEO satellite. Additionally, we consider a practical use case where satellite communication systems are deployed to increase coverage in remote and rural areas. For that purpose, we compare the coverage probability of the satellite-based communication system in such regions with the coverage probability in case of relying on the nearest anchored base station (ABS), which is usually located at far distances from rural and remote areas
  • Development of High-Mobility Low-Temperature Solution-Processed Metal-Oxide Thin Film Transistors Grown by Spray Pyrolysis

    Alsalem, Fahad K. (2020-07-08) [Thesis]
    Advisor: Anthopoulos, Thomas D.
    Committee members: Tung, Vincent; Shamim, Atif
    In today’s electronics, transistors are the main building blocks of the vast majority of electronic devices and integrated circuits. Types of transistors vary depending on the device structure and operation principle. Metal-oxide-based thin film transistors (MO TFTs), in particular, are an emerging technology that has a promising future in many applications, such as large-area display and wearable electronics. It exhibits unique features that make it superior to the existing Si-based technology, such as optical transparency and mechanical flexibility. However, some technical challenges in MO TFTs limit their emplyoment in today’s applications, such as low carrier mobility and high processing temperature. Solution-processed MO TFT based on spray pyrolysis combined with a carefully engineered TFT structure offers a dramatically enhance carrier mobility at low processing temperature. In this work, we are utilizing spray pyrolysis to grow In2O3 and ZnO based TFTs at low processing temperature. The structural effects of the channel layer on the electrical performance is investigated in two parts. The first part highlights the impact of thickness of the channel layer on the device performance of both In2O3 and ZnO, while the second part explores In2O3/ZnO heterojunction-based active layer. The results showed that increasing the channel thickness of both In2O3 and ZnO based TFTs enhanced the carrier mobility due to a reduced surface-roughness scattering effect. In addition, evidence showed that the electron transport mechanism in In2O3/ZnO heterojunction transitioned from trap-limited conduction (TLC) to percolation conduction (PC) process. Thanks to the existence of a 2D-confined electron sheet at the atomically sharp In2O3/ZnO heterointerface, the electron mobility was dramatically enhanced.

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