Stationary and Cyclostationary Processes for Time Series and Spatio-Temporal Data(2021-07-10) [Dissertation]
Advisor: Genton, Marc G.
Committee members: Stenchikov, Georgiy L.; Ombao, Hernando; Pourahmadi, MohsenDue essentially to the difficulties associated with obtaining explicit forms of stationary marginal distributions of non-linear stationary processes, appropriate characterizations of such processes are worked upon little. After discussing an elaborate motivation behind this thesis and presenting preliminaries in Chapter 1, we characterize, in Chapter 2, the stationary marginal distributions of certain non-linear multivariate stationary processes. To do so, we show that the stationary marginal distributions of these processes belong to specific skew-distribution families, and for a given skew-distribution from the corresponding family, a process, with stationary marginal distribution identical to that given skew-distribution, can be found. While conventional time series analysis greatly depends on the assumption of stationarity, measurements taken from many physical systems, which consist of both periodicity and randomness, often exhibit cyclostationarity (i.e., a periodic structure in their first- and second-order moments). Identifying the hourly global horizontal irradiances (GHIs), collected at a solar monitoring station of Saudi Arabia, as a cyclostationary process and considering the significant impact of that on the energy production in Saudi Arabia, Chapter 3 provides a temporal model of GHIs. Chapter 4 extends the analysis to a spatio-temporal cyclostationary modeling of 45 different solar monitoring stations of the Kingdom. Both the proposed models are shown to produce better forecasts, more realistic simulations, and reliable photovoltaic power estimates in comparison to a classical model that fails to recognize the GHI data as cyclostationary. Chapter 5 extends the notion of cyclostationarity to a novel and flexible class of processes, coined evolving period and amplitude cyclostationary (EPACS) processes, that allows periods and amplitudes of the mean and covariance functions to evolve and, therefore, accommodates a much larger class of processes than the cyclostationary processes. Thereafter, we investigate its properties, provide methodologies for statistical inference, and illustrate the presented methods using a simulation study and a real data example, from the heavens, of the magnitudes of the light emitted from the variable star R Hydrae. Finally, Chapter 6 summarizes the findings of the thesis and discusses its significance and possible future extensions.
Reconfigurable Snapshot HDR Imaging Using Coded Masks(2021-07-10) [Dissertation]
Advisor: Heidrich, Wolfgang
Committee members: Wonka, Peter; Ghanem, Bernard; Myszkowski, KarolHigh Dynamic Range (HDR) image acquisition from a single image capture, also known as snapshot HDR imaging, is challenging because the bit depths of camera sensors are far from sufficient to cover the full dynamic range of the scene. Existing HDR techniques focus either on algorithmic reconstruction or hardware modification to extend the dynamic range. In this thesis, we propose a joint design for snapshot HDR imaging by devising a spatially varying modulation mask in the hardware combined with a deep learning algorithm to reconstruct the HDR image. In this approach, we achieve a reconfigurable HDR camera design that does not require custom sensors, and instead can be reconfigured between HDR and conventional mode with very simple calibration steps. We demonstrate that the proposed hardware-software solution offers a flexible, yet robust, way to modulate per-pixel exposures, and the network requires little knowledge of the hardware to faithfully reconstruct the HDR image. Comparative analysis demonstrated that our method outperforms the state-of-the-art in terms of visual perception quality. We leverage transfer learning to overcome the lack of sufficiently large HDR datasets available. We show how transferring from a different large scale task (image classification on ImageNet) leads to considerable improvements in HDR reconstruction
Monitoring crop development and health using UAV-based hyperspectral imagery and machine learning(2021-07) [Dissertation]
Advisor: McCabe, Matthew
Committee members: Hong, Pei-Ying; Tester, Mark A.; Zarco-Tejada, PabloAgriculture faces many challenges related to the increasing food demands of a growing global population and the sustainable use of resources in a changing environment. To address them, we need reliable information sources, like exploiting hyperspectral satellite, airborne, and ground-based remote sensing data to observe phenological traits through a crops growth cycle and gather information to precisely diagnose when, why, and where a crop is suffering negative impacts. By combining hyperspectral capabilities with unmanned aerial vehicles (UAVs), there is an increased capacity for providing time-critical monitoring and new insights into patterns of crop development. However, considerable effort is required to effectively utilize UAV-integrated hyperspectral systems in crop-modeling and crop-breeding tasks. Here, a UAV-based hyperspectral solution for mapping crop physiological parameters was explored within a machine learning framework. To do this, a range of complementary measurements were collected from a field-based phenotyping experiment, based on a diversity panel of wild tomato (Solanum pimpinellifolium) that were grown under fresh and saline conditions. From the UAV data, positionally accurate reflectance retrievals were produced using a computationally robust automated georectification and mosaicking methodology. The resulting multitemporal UAV data were then employed to retrieve leaf-chlorophyll (Chl) dynamics via a machine learning framework. Several approaches were evaluated to identify the best-performing regression supervised methods. An investigation of two learning strategies (i.e., sequential and retraining) and the value of using spectral bands and vegetation indices (VIs) as prediction features was also performed. Finally, the utility of UAVbased hyperspectral phenotyping was demonstrated by detecting the effects of salt-stress on the different tomato accessions by estimating the salt-induced senescence index from the retrieved Chl dynamics, facilitating the identification of salt-tolerant candidates for future investigations. This research illustrates the potential of UAV-based hyperspectral imaging for plant phenotyping and precision agriculture. In particular, a) developing systematic imaging calibration and pre-processing workflows; b) exploring machine learning-driven tools for retrieving plant phenological dynamics; c) establishing a plant stress detection approach from hyperspectral-derived metrics; and d) providing new insights into using computer vision, big-data analytics, and modeling strategies to deal effectively with the complexity of the UAV-based hyperspectral data in mapping plant physiological indicators.
A single droplet auto-ignition of surrogate fuels, lubricant oil and their mixtures at elevated temperature and pressure(2021-07) [Dissertation]
Advisor: Roberts, William L.
Committee members: Sarathy, S. Mani; Knio, Omar Mohamad; Yang, YiPre-ignition is a type of irregular combustion that occurs in boosted direct injection gasoline engines when one or more auto-ignition events occur before to spark ignition. Due to the direct injection of fuel into the cylinder, some liquid fuel may splash off the walls, dragging along lubricating oil. The self-ignition of liquid fuel/lubricant droplets is one of the pre-ignition sources studied. To test this stochastic behavior in a controlled manner, we examined the auto-ignition of a single droplet of a hexadecane-fuel mixture, with hexadecane serving as a surrogate for the lub oil. This experiment involved suspending a single hexadecane-fuel mixture droplet on a thermocouple bead in preheated air at temperatures ranging from 150 to 300 ° C over a wide range of pressures (4-30 bar). Various fuels with RON values ranging from 0 to 120 were blended with hexadecane at varying volume percentages of fuel in hexadecane from 0% to 100% to determine the droplet's time to ignition, denoted by TI. TI was determined by concurrently recording the history of the droplet temperature and imaging it at high speed. The ignition of the droplet is triggered by the self-ignition of the combustible mixture created by the vapor of the hexadecane-fuel mixture reacting with the heated ambient air surrounding the droplet. The increase in RON increased the TI as high RON fuels are difficult to ignite. However, the TI of the mixture depended on the fuel mixture properties even when the RON of the mixture was relatively high. Furthermore, the metal additives were added to the oil surrogate to investigate their effect on getting a pre-ignition event. The lubricant oil additives were phosphate, magnesium, and calcium. These additives were mixed with hexadecane at different concentrations. The experiments were conducted in a constant volume combustion chamber at 300 ⁰C temperature and the pressure was varied from 5 to 15 bar. The resulting TI were then compared with the TI of pure hexadecane. The results showed that addition of phosphate reduces the chances of getting a pre-ignition event, magnesium showed neutral effect while calcium enhanced the chances of getting a pre-ignition event.
Unraveling the Microstructure of Organic Electrolytes for Applications in Lithium-Sulfur Batteries(2021-06-30) [Dissertation]
Advisor: Anthopoulos, Thomas D.
Committee members: Tung, Vincent; Hadjichristidis, Nikos; Xu, KangLithium batteries have revolutionized emerging electronic applications and will play more important roles in the future. Unfortunately, the energy density of commercial lithium-ion batteries (100-265 Wh kg-1) cannot satisfy the fast-growing demand for energy storage technologies. Lithium-sulfur (Li-S) batteries stand out for high energy density (2567 Wh kg-1), low-cost, and environmentally benign attributes. However, the development of Li-S full-batteries is still hindered by the dissolution of polysulfides into the organic electrolytes and poor ions transfer at the interfaces of electrolytes and lithium-intercalated electrodes (e.g., lithiated graphite). Improving the electrolytes is a crucial aspect for the development of battery technologies, but the knowledge concerning the electrolyte microstructures remains elusive. This dissertation unravels the microstructures of organic electrolytes and paves the way to the development of Li-S batteries. Firstly, we demonstrate the key role of electrolyte chemistry in the battery performances by showing a synergetic effect of electrolytes coupled with designed sulfur cathodes. Secondly, we investigate the microstructure of electrolytes and discover previously unexplored solvent-solvent and solvent-anion interactions. We show that the interactions are useful to elucidate important battery operations, such as ions transfer at electrolyte-electrode interfaces, and reveal a potential probe for developing battery electrolytes. Thirdly, we optimize the electrolyte composition to obtain a highly reversible Li+ intercalation/deintercalation at the graphite anode, giving high performances of Li-S full-batteries in a dilute electrolyte concentration. Finally, we unravel the key role of additives in suppressing Li+ solvation in the electrolytes. Nitrate (NO3-) anions are observed to incorporate into the solvation shells, change the local environment of Li+ cations, and then lead to an effective Li+ desolvation followed by improved battery performances. Key significances of this dissertation are (i) observation of detailed electrolyte microstructures showing a potential probe for developing battery electrolytes; (ii) evidences of the electrolyte chemistry plays a predominant role in the electrolyte-electrode interfacial reactions, which prevails over the role of commonly believed solid electrolyte interphase (SEI); and (iii) new mechanistic insights into the key role of additives in the electrolyte microstructures. Furthermore, the presented methodology paves the way for developing electrolytes for broad electrochemical applications.
Cylindrical Nanowires for Water Splitting and Spintronic Devices(2021-06-10) [Dissertation]
Advisor: Kosel, Jurgen
Committee members: Zhang, Xixiang; Manchon, Aurelien; Fariborzi, Hossein; Vazquez, ManuelEnergy enables basic and innovative services to reach a seemingly ever-growing population and when its generation costs are reduced or when its usage is optimized it has the greatest impact on the reduction of poverty. Furthermore, there is a pressing need to decouple energy generation from non-renewable and carbon-heavy sources which has led mayor economies to increase research efforts in these areas. This thesis discusses research on water oxidation using nanostructured iron oxide electrodes and current-induced magnetic domain wall motion in nickel/cobalt bi-segmented nanowires. These two fields may seem disparate at first glance, but are linked by such common theme: materials for energy, and more precisely, materials for energy conversion and economy. The work presented in this document aims also to reflect this theme by using widely available materials like iron and aluminum, and optimizing the methods to produce the final samples using the least resources possible. All samples were prepared by electroplating metals (iron, cobalt and nickel) into anodized alumina templates fabricated inhouse. For water oxidation, iron nanorods were integrated into an electrode and annealed in air, while nickel/cobalt nanowires were isolated and contacted individually to test for spintronics-related effects. Spintronic-based devices aim to reduce energy usage in nowadays microelectronic devices. The nanostructured iron oxide electrode showed its usefulness for water oxidation in a laboratory environment, making it an appropriate complement to other electrodes specially designed for water reduction in a photoelectrochemical cell. This two-electrode design, allows for hydrogen and oxygen to be produced at each electrode and therefore eases their separate collection for, e.g., fuel or fertilizers. On the other hand, this work presents one of the first experimental demonstration of current-induced domain wall motion in soft/hard cylindrical magnetic nanowires at zero applied external magnetic field. These kinds of experiments are expected to be the first of many which will allow researchers in the field to test for spintronic-relevant properties and interactions in cylindrical magnetic nanowires.
New Strategies for High Efficiency Perovskite Single Crystal Solar Cells and Stable Luminescent Inorganic Materials(2021-06-08) [Dissertation]
Advisor: Bakr, Osman
Committee members: Ooi, Boon S.; Mohammed, Omar F.; Alshareef, Husam N.; Kovalenko, MaksymMetal halide perovskite semiconductors offers bright future for optoelectronic applications due to their excellent optical and electrical properties and their low-cost solution-based facile fabrication. The most of the perovskite application are based on the defective polycrystalline films and they offer inadequate moisture/thermal chemical stability. Therefore, this dissertation is dedicated to find new strategies to deploy the single-crystal perovskites to photovoltaics and new methods to reduce the moisture/thermal instability of inorganic perovskite light-emitters. In first part of this dissertation, we aimed to reveal the potential of the single crystal in photovoltaics. Single-crystal semiconductors can outperforms their polycrystalline forms in terms of photovoltaic performance due to their better structural quality and less electronic traps. However, the most efficient perovskite solar cells are based on polycrystalline films. While single crystals can perform beyond the limits of polycrystalline films, their synthesis and device integration are complex. Therefore, we aimed to create new synthetic methods to unveil the potential of the single-crystal perovskites in photovoltaics. We developed new strategies leading the perovskite single crystals to go beyond 20% power conversion efficiency in Chapter 2. Also fundamental limits of the perovskite single crystals are investigated in Chapter 3 by fabricating single crystal cells with varying thicknesses, and the electron diffusion length is calculated to be 520 μm. In Chapter 4, we propose surface modification and compositional engineering techniques to bring the perovskite single crystal photovoltaic one step beyond of the previous point by reaching 21.9% and 22.8% efficiencies, respectively. In the second part of this dissertation (Chapter 5), a novel synthetic method is offered to achieve highly stable light-emitting perovskite-related materials since the fast degradation of perovskites in the presence of water and moisture is a challenge for perovskite-based technologies and hinders the material’s potential. We demonstrated that these a direct transformation of 3D CsPbBr3 films to CsPb2Br5 exhibiting excellent stability against humidity and heat while keeping the high photoluminescence quantum yield. We believe the strategies offered in this dissertation will open an avenue in photovoltaic and light emitting applications, and can be utilized in new optoelectronic applications in future.
Synthesis and Characterization of Novel Self-Assembling Tetrapeptides for Biomedical Applications and Tissue Engineering(2021-06) [Dissertation]
Advisor: Hauser, Charlotte
Committee members: Huang, Kuo-Wei; Jaremko, Mariusz; Guler, Mustafa O.Molecular self-assembly is the process of molecules able to associate into more ordered structures. Examples of self-assembling molecules is a class of ultrashort amphiphilic peptides with a distinct sequence motif, which consist of only three to seven amino acids. These peptides can self-assemble to form nanofibrous scaffolds, such as in form of hydrogels, organogels or aerogels, due to their amphiphilic structure which contains a dominant hydrophobic tail and a polar head group. Interestingly, these peptide scaffolds offer a remarkably similar fiber topography to that one found in collagen which is a dominant part of the extracellular matrix. The resemblance to collagen fibers brings a potential benefit in using these peptide scaffolds together with native human cells. Specifically, they can maintain high water content over 99 % weight per volume and are suitable for tissue engineering and regenerative medicine applications. Over the last decade, they have shown promising therapeutic potential in treating several diseases thanks to their high activity, target specificity, low toxicity, and minimal nonspecific and drug-drug interactions. This dissertation describes how to characterize and use ultrashort amphiphilic peptides for tissue engineering and biomedicine. The first chapter offers an overview of already reported self-assembling ultrashort peptides and their applications. As a proof-of-concept, ultrashort peptide scaffolds were used for osteogenic differentiation. Peptide nanoparticles were embedded into 5 peptide hydrogels with the goal to tune the stiffness of the peptide gels. Furthermore, the peptide scaffold was used for the generation of gold and silver nanoparticles after UV irradiation, which allowed the production of nanoparticles in the absence of any additional reducing agent. The mechanism of the generation of these nanoparticles was then investigated. The last chapter describes how tetrameric peptide solutions were utilized for 3D bioprinting applications. Compared to earlier reported self-assembling ultrashort peptide compounds, these tetrapeptides can form hydrogels at an extremely low concentration of 0.1% w/v in a relatively short time under physiological conditions. These promising findings suggest that the peptide solutions are promising bioinks for use in 3D bioprinting.
Computational Wavefront Sensing: Theory, Practice, and Applications(2021-06) [Dissertation]
Advisor: Heidrich, Wolfgang
Committee members: Ghanem, Bernard; Wonka, Peter; Waller, LauraWavefront sensing is a fundamental problem in applied optics. Wavefront sensors that work in a deterministic manner are of particular interest. Initialized with a unified theory for classical wavefront sensors, this dissertation discusses relevant properties of wavefront sensor designs. Based on which, a new wavefront sensor, termed Coded Wavefront Sensor, is proposed to leverage the advantages of the analysis, especially the lateral wavefront resolution. A prototype was built to demonstrate this new wavefront sensor. Given that, two specific applications are demonstrated: megapixel adaptive optics and simultaneous intensity and phase imaging. Combined with a spatial light modulator, a hardware deconvolution approach is demonstrated for computational cameras via a high resolution adaptive optics system. By simply switching the normal image sensor with the proposed one, as well as slight change of illumination, a bright field microscope can be configured to a simultaneous intensity and phase microscope. These show the broad application range of the proposed computational wavefront sensing approach. Lastly, this dissertation proposes the idea of differentiable optics for wavefront engineering and lens metrology. By making use of automatic differentiation, a physically-correct differentiable ray tracing engine is built, with its potentials being illustrated via several challenging applications in optical design and metrology.
Studies of Preignition in Homogeneous Environments(2021-06) [Dissertation]
Advisor: Farooq, Aamir
Committee members: Roberts, William L.; Thoroddsen, Sigurdur T; Santamarina, Carlos; Heufer, Karl AlexanderPreignition is an ignition event that happens before it is expected to happen and, many times, where it is not expected to happen. Understanding this phenomenon is of great importance as it influences the design and operation of modern downsized boosted internal combustion engines. To gain a fundamental understanding of preignition, homogeneous reactors like shock tubes and rapid compression machines may be used to decipher the influence of fuel chemical structure, temperature, pressure, equivalence ratio and bath gas on preignition. In this thesis, a comprehensive study of the preignition tendency of various chemical systems is presented. Firstly, renewable fuels like ethanol, methanol and a surrogate of conventional fuels, n-hexane, are characterized by traditional shock tube techniques, such as the measurements of ignition delay times and pressure-time histories, to identify thermodynamic conditions which promote non-ideal ignition behavior. Preignition pressure rise and the expedition of measured ignition delay times are identified as the indicators of non-homogeneous combustion. It is shown that preignition effects are more likely to be observed in mixtures containing higher fuel concentration and that preignition energy release is more pronounced at lower temperatures. High-speed imaging was implemented to visualize the combustion process taking place inside the shock tube. End-wall imaging showed that low-temperature ignition may be initiated from an individual hot spot that grows gradually, while high-temperatures ignition starts from many spots simultaneously which consume the reactive mixture almost homogeneously. Simultaneous lateral and endwall imaging was implemented in both low- and high-pressure shock tube facilities. All tested fuels exhibited localized ignition at low temperatures, and methanol showed a higher propensity than ethanol to ignite far from the endwall. Imaging experiments were also performed in a rapid compression machine to understand preignition at lower temperatures. Herein, ethanol showed non-homogeneous ignition while iso-octane and diethyl ether exhibited homogeneous ignition at the low-temperature conditions. Various criteria for the onset of preignition were tested against experimental observations to propose an adequate predictor of non-ideal ignition phenomena in practical applications. A non-dimensional number, relating the ignition delay sensitivity and laminar flame speed of the mixtures, was found to be the best criterion to elucidate ignition regimes.
Toward Controlled Growth of Two-Dimensional Transition Metal Dichalcogenides: Chemical Vapor Deposition Approaches(2021-05-13) [Dissertation]
Advisor: Tung, Vincent
Committee members: Anthopoulos, Thomas D.; Ooi, Boon S.; Li, Sean; Li, LanceRecently, atomically thin two-dimensional (2D) transition metal dichalcogenides (TMDCs) materials have drawn significant attention due to their unique optical and electrical properties1, 2. This offers unique opportunities for the next-generation electronic and optoelectronic devices3. Specifically, recent innovations in the big-data-driven prediction of new 2D materials, integration of new device architectures, interfacial engineering of contacts between semiconductor/metals and semiconductor/dielectrics as well as encapsulation in hexagonal boron nitride4, 5 have further propelled the electrical mobility to be on a par with or even beyond the silicon (Si) counterpart. These strategies hold tantalizing prospects on extending the Moore's law. Yet, there is still room for improvement before 2D TMDCs become truly technologically relevant. The challenge lies in the full validation of the intrinsic charge transport that is associated with the specific nature and ordered arrangement of atoms in the atomically thin crystal lattice. This requires, the controlled stitch of both metals and chalcogenides in an atom-by-atom fashion. To this end, a variety of synthetic approaches have been developed, this includes but not limited to chemical vapor deposition (CVD) 6, 7, mechanical exfoliation8 and solution-based exfoliation9. Among which, CVD shows better controllability over thicknesses, geometric shapes, sizes, and qualities through manipulation of the growth factors, e.g., growth temperature, pressure, precursor ratio, and gas carrier. These complex growth environments will significantly confound the scalability, crystallinity, defect density, and reproducibility of the CVD approach. Therefore, an impetus exists to gain fundamental insights into the universal growth mechanism that is currently lacking and therefore curbs the realization o the controlled epitaxy of high-mobility three-atom-thick semiconducting TMDCs films with wafer-scale-homogeneity. In this thesis, a mechanistic study toward revealing the epitaxy growth mechanism is established to include 1) epitaxy growth of multilayer, 2) epitaxy growth of heterostructures, and 3) epitaxy growth of high quality (exceedingly low defect density) of 2D TMDCs materials through a controlled CVD strategy.
Interface engineering of high performance organic and perovskite solar cells(2021-05) [Dissertation]
Advisor: Anthopoulos, Thomas D.
Committee members: Laquai, Frédéric; McCulloch, Iain; Heeney, MartinBoth organic and perovskite solar cells (OSCs and PSCs, respectively) have shown remarkable progress in recent years reaching power conversion efficiencies (PCEs) of 17.6% and 25.2% for a single cell, respectively. These results were achieved by simultaneous advancements in organic and perovskite materials design and synthesis, as well as device and interfacial engineering. As these emerging photovoltaic technologies move closer to commercialization, further improvements in efficiencies and stability of the solar cells are needed. Interfaces in these thin-film solar cells have proven to be of tremendous importance for both device performance and degradation. This work is focused on studying recombination losses at the charge extracting layers in OSCs and PSCs and finding simple solution-processable ways of improving interfacial contacts. In the first part, we propose a simple way to improve the electron extracting properties of Phen-NaDPO, a small organic molecule widely used in OSCs, by mixing it with Sn(SCN)2. We show that this approach benefits morphology and charge transport, thus reducing recombination losses and improving overall performance of various bulk heterojunction OSCs and PSCs. In the second part, we describe the development of a multilayered system of electron transporting interlayers (ETLs) to improve the PCE and operational stability of PSCs. We sequentially deposit PC60BM, Al-doped ZnO (AZO), and small organic molecule triphenyl-phosphine oxide (TPPO), and study how the ETL properties and device performance change with each layer. We find that the trap-assisted recombination and energy level alignment in PSCs improve due to specific chemical interactions between PC60BM, AZO, and TPPO. The third part is divided into two and is focused on CuSCN, a wide bandgap inorganic molecular hole transporting material, and its application in OSCs. In the first half, we study the recombination and photogeneration processes in PC70BM-only OSCs. We demonstrate that CuSCN plays a crucial role in excitons dissociation and efficient charge transfer at the CuSCN/PC70BM interface. In the second half, we optimize CuSCN layers’ structural and electronic characteristics using a simple solvent engineering approach. We study how processing conditions affect the morphological, chemical, optical, and electronic properties of CuSCN and how they impact the OSCs’ performance.
Functional Metal Organic Frameworks for Surface Organometallic Chemistry and Carbon Conversion(2021-05) [Dissertation]
Advisor: Eddaoudi, Mohamed
Committee members: Basset, Jean-Marie; Ruiz-Martinez, Javier; Astruc, DidierAbstract: Metal-Organic Frameworks (MOFs) are a class of highly porous, hybrid, functional and crystalline extended coordination compounds. Their exceptional properties renders them ideal for a wide range of applications including gas storage and catalysis. Especially for catalysis, MOFs are receiving attention as well-defined supports for organometallic heterogeneous catalysis with noticeably the post-synthetic grafting of transition metal complexes on secondary building units (SBU) containing hydroxides moieties. The objective of this dissertation is to explore the synthesis, reactivity and functionalization of MOFs with SBU containing hydroxides units by transition metal catalyst using the Surface Organometallic Chemistry (SOMC) approach. Chapter 1, gives an introduction to the field of MOF and their applications to catalysis through the functionalization of hydroxide containing SBUs. This chapter introduces also the SOMC strategy with an overview of its catalytic application for olefin metathesis and CO2 conversion. Chapter 2 and 3 give a detailed application of SOMC to MOFs with the selective grafting of the W(≡CtBu)(CH2tBu)3 complex on the highly crystalline and mesoporous Zr-NU-1000 MOF. The obtained single site material, Zr-Nu-1000-W, is fully characterized using state of the art experimental methods and all the steps leading to the final grafted moieties were identified by DFT. Zr-NU-1000-W is active for olefin metathesis and is further fine-tuned by activation with EtAlCl2 giving a more selective and stable catalyst. Moreover, the nature of the grafted species could be modulated by pre-activation of the initial W(≡CtBu)(CH2tBu)3 complex with dmpe giving W(≡CtBu)(=CHtBu)(CH2tBu)(dmpe) also grafted on Zr-NU-1000. Chapter 4 and 5, describe the deliberate design and bulk synthesis of a new zirconium MOF, Zr-she-MOF-2, and highlight the discovery of a new highly connected MOF, RE-urx-MOF-1, based on a careful combination of rare earth (RE) metals with heterobifunctional triangular tetrazolate-based ligand. Additionally, the replacement of the tetrazolate functionality by carboxylate, leads to the formation of a different MOF structure RE-gea-MOF-4 having the gea topology with the presence of 18-connected nonanuclear RE cluster. Both Zr-she-MOF-2 and RE-gea-MOF-4 are active for the coupling of epoxides with CO2 to form cyclic carbonate in the presence of Bu4NBr. Finally, Chapter 6 will discuss the conclusions and perspectives of this dissertation.
Theoretical and Experimental Investigations of the Dynamics of Axially Loaded - Microstructures with Exploitation for MEMS Resonator-Based Logic Devices(2021-05) [Dissertation]
Advisor: Younis, Mohammad I.
Committee members: Farooq, Aamir; Fariborzi, Hossein; Caruntu, DumitruIn line with the rising demand for smarter solutions and embedded systems, Microelectromechanical systems (MEMS) have gained increasing importance for digital computing devices and Internet-of-Things (IoT) applications, most notably for mobile wearable devices. This achievement is driven by MEMS resonators' inherent properties such as simplicity, sensitivity, reliability, and low power consumption. Hence, they are being explored for ultra-low-power computing machines. Several fundamental digital logic gates, switching, and memory devices have been demonstrated based on MEMS microstructures' static and dynamic behavior. The interest of researchers in using MEMS resonators is due to seeking an alternative approach to circumvent the notable current leakage and power density problems of complementary metal-oxide-semiconductor (CMOS) technology. The continuous miniaturization of CMOS has increased the operating speed and reduces the size of the device. However, this has led to a relative increase in the leakage energy. This drawback in CMOS has renewed the interest of researchers in mechanical digital computations, which can be traced back to the work of Charles Babbage in 1822 on calculating engines. This dissertation presents axially-loaded and coupled-MEMS resonators investigations to demonstrate memory elements and different logic functions. The studies in this dissertation can be categorized majorly into three parts based on the implementation of logic functions using three techniques: electrothermal frequency tunability, electrostatic frequency modulations, and activation/deactivation of the resonant frequency. Firstly, the influence of the competing effects of initial curvature and axial loads on the mechanical behavior of MEMS resonator arches are investigated theoretically to predict the tunability of arches under axial loads. Then, the concept of electrothermal frequency tunability is used to demonstrate fundamental 2-bit logic gates. However, this concept consumes a considerable amount of energy due to the electrothermal technique. Next, the dynamic memory element and combinational logic functions are demonstrated using the concept of electrostatic frequency modulation. Though this approach is energy efficient compared to the electrothermal technique, it does not support the cascadability of MEMS resonator-based logic devices. Lastly, complex multifunctional logic gates are implemented based on selective modes activation and deactivation, resulting in significant improvement in energy efficiency and enabling cascadability of MEMS resonator-based logic devices.
Toward Improving the Internet of Things: Quality of Service and Fault Tolerance Perspectives(2021-04-13) [Dissertation]
Advisor: Shihada, Basem
Committee members: Alouini, Mohamed-Slim; Zhang, Xiangliang; Bessani, AlyssonThe Internet of Things (IoT) is a technology aimed at developing a global network of machines and devices that can interact and communicate with each other. Supporting IoT, therefore, requires revisiting the Internet's best e ort service model and reviewing its complex communication patterns. In this dissertation, we explore the unique characteristics of IoT tra c and examine IoT systems. Our work is motivated by the new capabilities o ered by modern Software De ned Networks (SDN) and blockchain technology. We evaluate IoT Quality of Service (QoS) in traditional networking. We obtain mathematical expressions to calculate end-to-end delay, and dropping. Our results provide insight into the advantages of an intelligent edge serving as a detection mechanism. Subsequently, we propose SADIQ, SDN-based Application-aware Dynamic Internet of things QoS. SADIQ provides context-driven QoS for IoT applications by allowing applications to express their requirements using a high-level SQL-like policy language. Our results show that SADIQ improves the percentage of regions with an error in their reported temperature for the Weather Signal application up to 45 times; and it improves the percentage of incorrect parking statuses for regions with high occupancy for the Smart Parking application up to 30 times under the same network conditions and drop rates. Despite centralization and the control of data, IoT systems are not safe from cyber-crime, privacy issues, and security breaches. Therefore, we explore blockchain technology. In the context of IoT, Byzantine fault tolerance-based consensus protocols are used. However, the blockchain consensus layer contributes to the most remarkable performance overhead especially for IoT applications subject to maximum delay constraints. In order to capture the unique requirements of the IoT, consensus mechanisms and block formation need to be redesigned. To this end, we propose Synopsis, a novel hierarchical blockchain system. Synopsis introduces a wireless-optimized Byzantine chain replication protocol and a new probabilistic data structure. The results show that Synopsis successfully reduces the memory footprint from Megabytes to a few Kilobytes with an improvement of 1000 times. Synopsis also enables reductions in message complexity and commitment delay of 85% and 99.4%, respectively.
LITHIUM-SULFUR BATTERY DESIGN: CATHODES, SEPARATORS, AND LITHIUM METAL ANODES(2021-04-04) [Dissertation]
Advisor: Lai, Zhiping
Committee members: Huang, Kuo-Wei; Alshareef, Husam N.; Li, Lain-JongThe shortage of energy sources and the global climate change crisis have become critical issues. Solving these problems with clean and sustainable energy sources (solar, wind, tidal, and so on) is a promising solution. In this regard, energy storage techniques need to be implemented to tackle with the intermittent nature of the sustainable energies. Among the next-generation energy storage systems, lithium sulfur batteries has gained prominence due to the low cost, high theoretical specific-capacity of sulfur. Extensive research has been conducted on this battery system. Nevertheless, several issues including the “shuttle effect” and the growth of lithium dendrites still exist, which could cause rapid capacity loss and safety hazards. Several methods are proposed to tackle the challenges in this dissertation, including cathode engineering, interlayer design, and lithium metal anode protection. An asymmetric cathode structure is first developed by a non-solvent induced phase separation (NIPS) method. The asymmetric cathode comprises a nanoporous matrix and ultrathin and dense top layer. The top-layer is a desired barrier to block polysulfides transport, while the sublayer threaded with cationic networks facilitate Li-ions transport and sulfur conversions. In addition, a conformal and ultrathin microporous membrane is electrodeposited on the whole surface of the cathode by an electropolymerization method. This strategy creates a close system, which greatly blocks the LiPS leakage and improves the sulfur utilization. A polycarbazole-type interlayer is deposited on the polypropylene (PP) separator via an electropolymerization method. This interlayer is ultrathin, continuous, and microporous, which defines the critical properties of an ideal interlayer that is required for advanced Li–S batteries. Meanwhile, a self-assembled 2D MXene based interlayer was prepared to offer abundant porosity, dual absorption sites, and desirable electrical conductivity for Li-ions transport and polysulfides conversions. A new 2D COF-on-MXene heterostructures is prepared as the lithium anode host. The 2D heterostructures has hierarchical porosity, conductive frameworks, and lithiophilic sites. When utilized as a lithium host, the MXene@COF host can efficiently regulate the Li+ diffusion, and reduce the nucleation and deposition overpotential, which results in a dendrite-free and safer Li–S battery.
Wireless Magnetic Sensors to Empower the Next Technological Revolution(2021-04) [Dissertation]
Advisor: Kosel, Jürgen
Committee members: Salama, Khaled N.; Alshareef, Husam N.; Al Attar, Talal; Sonkusale, SameerThe next technological revolution, Industry 4.0, is envisioned as a digitally connected ecosystem where machines and gadgets are driven by artificial intelligence. By 2025, more than 75 billion devices are projected to serve this revolution. Many of which are to be integrated into the fabrics of everyday life in the form of smart wireless sensors. Still, two major challenges should be addressed to realize truly wireless and wearable sensors. First, the sensors should be flexible and stretchable, allowing for comfortable wearing. Second, the electronics should scavenge the energy it requires entirely from the environment, thus, eliminating the need for batteries, which are bulky, create ecological problems, etc. By addressing these two challenges, this dissertation paves the way for truly wearable sensors. The first part of the dissertation introduces a biocompatible magnetic skin with exceptional physical properties. It is highly-flexible, breathable, durable, and realizable in any desired shape and color. Attached to the skin of a user, the magnetic skin itself does not require any wiring, allowing to place the electronics and delicate components of the wireless sensor in a convenient nearby location to track the magnetic field produced by the magnetic skin. To demonstrate the performance of the magnetic skin, wearable systems are implemented as an assistive technology for severe quadriplegics, a touchless control solution for eliminating cross contaminations, and for monitoring blinking and eye movement for sleep laboratories. The second part of the dissertation is about wirelessly powering wireless sensors. In doing so, radio frequency (RF) rectifiers are a bottleneck, especially for ambient RF energy harvesting. Therefore, two RF rectifiers are introduced in standard CMOS technologies. The first architecture utilizes double-sided diodes to reduce the reverse leakage current, thus achieving a high dynamic range of 6.7 dB, -19.2 dBm sensitivity, and 86% efficiency. The second rectifier implements a dual-mode technique to lower the effective threshold voltage by 37%. Consequently, it achieves a 38% efficiency at −35 dBm input power and a 10.1 dB dynamic range while maintaining the same efficiency and sensitivity. Ultimately, combining these wireless powering techniques with the magnetic skin allows for truly wireless and wearable solutions.
Discriminant Analysis and Support Vector Regression in High Dimensions: Sharp Performance Analysis and Optimal Designs(2021-04) [Dissertation]
Advisor: Alouini, Mohamed-Slim
Committee members: Shihada, Basem; Zhang, Xiangliang; Kammoun, Abla; McKay, MatthewMachine learning is emerging as a powerful tool to data science and is being applied in almost all subjects. In many applications, the number of features is com- parable to the number of samples, and both grow large. This setting is usually named the high-dimensional regime. In this regime, new challenges arise when it comes to the application of machine learning. In this work, we conduct a high-dimensional performance analysis of some popular classification and regression techniques. In a first part, discriminant analysis classifiers are considered. A major challenge towards the use of these classifiers in practice is that they depend on the inverse of covariance matrices that need to be estimated from training data. Several estimators for the inverse of the covariance matrices can be used. The most common ones are estimators based on the regularization approach. In this thesis, we propose new estimators that are shown to yield better performance. The main principle of our proposed approach is the design of an optimized inverse covariance matrix estimator based on the assumption that the covariance matrix is a low-rank perturbation of a scaled identity matrix. We show that not only the proposed classifiers are easier to implement but also, outperform the classical regularization-based discriminant analysis classifiers. In a second part, we carry out a high-dimensional statistical analysis of linear support vector regression. Under some plausible assumptions on the statistical dis- tribution of the data, we characterize the feasibility condition for the hard support vector regression and, when feasible, derive an asymptotic approximation for its risk. Similarly, we study the test risk for the soft support vector regression as a function of its parameters. The analysis is then extended to the case of kernel support vector regression under generalized linear models assumption. Based on our analysis, we illustrate that adding more samples may be harmful to the test performance of these regression algorithms, while it is always beneficial when the parameters are optimally selected. Our results pave the way to understand the effect of the underlying hyper- parameters and provide insights on how to optimally choose the kernel function.
Programmable materials for sensors, actuators and manipulators for soft robotics applications(2021-04) [Dissertation]
Advisor: Lubineau, Gilles
Committee members: Lacoste, Deanna; Blilou, Ikram; Leng, JinsongThis thesis describes the concept of programmable materials with tunable physical properties applicable to soft robots. We present these materials for three major applications in soft robotics: sensing, actuation, and robotic manipulation. The strain sensors recognize the internal stimuli in a soft robot, whereas the conductors collect the sensors’ signals to the control part. In the first part, we want to develop both stretchable strain sensors and conductors from a single material by programming a nanowire network’s electrical property, which we achieve through Electrical Welding (e-welding). We demonstrate the transformation of a Silver Nanowire (AgNW)-polymer sponge from a strain sensor to a stretchable conductor through e-welding. Using this method, we produced a soft hybrid e-skin having both a sensor and conductor from a single material. In the second part, we propose new active actuation solutions by obtaining quick, tunable pressure inside a soft material that we achieve through a liquid-gas phase transition of a stored liquid using an efficient electrode. We discuss the significant design variables to improve the performance and propose a new design for the electrodes, for enhancing actuation speed. We propose using low voltage equipment to trigger the phase transition to produce compact actuation technology for portable applications. Using this method, we produced a portable soft gripper. In the third and last part, we want to develop a simple robotic manipulation technology using a single-chambered soft body instead of a multi-chambered system. We propose using on-demand stiffness change in soft material to control the shape change of a single-chambered soft body. For this, we introduce a new concept of a stiffness tunable hybrid fiber: a fiber with stiff and soft parts connected in a series. We demonstrate a substantial change in membrane stiffness in the fiber through locking/unlocking of the soft part of the fiber. We integrated these fibers into a pneumatically operated single-chambered soft body to control its stiffness for on-demand shape change. If applied together, these three concepts could result in a fully printable, cheap, light, and easily controllable new generation soft robots with augmented functionalities.
Generation of Orbital Angular Momentum (OAM) Modes with a Spiral Phase Plate Integrated Laser Source(2021-04) [Dissertation]
Advisor: Ooi, Boon S.
Committee members: Alouini, Mohamed-Slim; Liberale, Carlo; Forbes, AndrewThe objective of this work is to develop a near-infrared laser device capable of emitting orbital angular momentum (OAM) light. The prototyped device must be suitable for compact, energy-saving optical communication applications. Integrated OAM lasers will revolutionize high-capacity data transmission over any telecommuni- cation network environment, as OAM light can be guided and transmitted through kilometers of optical fibers and propagated in free space and underwater. Several methods for generating OAM light employing various complex monolithic and hybrid integration methods have been demonstrated. In this work, microscale integrated spiral phase plates (SPPs) are chosen to convert the laser beam output into an OAM mode. The concept and design fundamentals of SPPs are discussed, followed by the SPP fabrication process and their implementation in a high-speed communication setup and then integration with a semiconductor laser. SPPs are fabricated by a novel direct laser writing that provides the possibility to rapidly prototype 3D photonic structures via a two-photon polymerization pro- cess. After fabrication, SPPs are used in a fine-tuned free-space optical experimental setup that requires high-precision intercomponent alignment to test the high-speed OAM communication system and analyze the quality of OAM modes, resulting in high-purity OAM signals at data rates up to 1.8 Gbit/s – limited by the avalanche photodetector (APD) frequency response. The fabricated 20-μm-diameter SPPs were the smallest reported in the literature to date for optical characterization. A proof-of-concept monolithic light-emitting array, as a highly integrated OAM laser source, is further proposed for telecommunications and other applications. SPP-integrated 940-nm vertical-cavity surface-emitting laser (VCSEL) array chips that are relatively low-cost, have a small footprint, and are manufacturable in high volumes are developed. SPPs with topological charge modulus values from 1 to 3 are fabricated on the VCSEL arrays, demonstrating OAM modal purities up to ∼65%. The experimentally evaluated data rates in the OAM setup showed consistently sta- ble links up to 2.0 Gbit/s with a bit error ratio of ∼ 1.6 × 10−8 (APD-limited). The challenges of SPP-laser integration are summarized, with the conclusion that the widespread adoption of OAM is limited by the availability of practical integrated solutions for OAM generation and detection.