Theses and Dissertations
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Lagrangian Spatio-Temporal Covariance Functions for Multivariate Nonstationary Random Fields(2021-06-14) [Thesis]
Advisor: Genton, Marc G.
Committee members: Ombao, Hernando; Sang, Huiyan; Stenchikov, Georgiy L.In geostatistical analysis, we are faced with the formidable challenge of specifying a valid spatio-temporal covariance function, either directly or through the construction of processes. This task is di cult as these functions should yield positive de nite covariance matrices. In recent years, we have seen a ourishing of methods and theories on constructing spatiotemporal covariance functions satisfying the positive de niteness requirement. The current state-of-the-art when modeling environmental processes are those that embed the associated physical laws of the system. The class of Lagrangian spatio-temporal covariance functions ful lls this requirement. Moreover, this class possesses the allure that they turn already established purely spatial covariance functions into spatio-temporal covariance functions by a direct application of the concept of Lagrangian reference frame. In the three main chapters that comprise this dissertation, several developments are proposed and new features are provided to this special class. First, the application of the Lagrangian reference frame on transported purely spatial random elds with second-order nonstationarity is explored, an appropriate estimation methodology is proposed, and the consequences of model misspeci cation is tackled. Furthermore, the new Lagrangian models and the new estimation technique are used to analyze particulate matter concentrations over Saudi Arabia. Second, a multivariate version of the Lagrangian framework is established, catering to both secondorder stationary and nonstationary spatio-temporal random elds. The capabilities of the Lagrangian spatio-temporal cross-covariance functions are demonstrated on a bivariate reanalysis climate model output dataset previously analyzed using purely spatial covariance functions. Lastly, the class of Lagrangian spatio-temporal cross-covariance functions with multiple transport behaviors is presented, its properties are explored, and its use is demonstrated on a bivariate pollutant dataset of particulate matter in Saudi Arabia. Moreover, the importance of accounting for multiple transport behaviors is discussed and validated via numerical experiments. Together, these three extensions to the Lagrangian framework makes it a more viable geostatistical approach in modeling realistic transport scenarios.
Flexible Covariance Models for Spatio-Temporal and Multivariate Spatial Random Fields(2021-06-06) [Thesis]
Advisor: Sun, Ying
Committee members: Alouini, Mohamed-Slim; Ombao, Hernando; Kleiber, WilliamThe modeling of spatio-temporal and multivariate spatial random elds has been an important and growing area of research due to the increasing availability of spacetime- referenced data in a large number of scienti c applications. In geostatistics, the covariance function plays a crucial role in describing the spatio-temporal dependence in the data and is key to statistical modeling, inference, stochastic simulation and prediction. Therefore, the development of exible covariance models, which can accomodate the inherent variability of the real data, is necessary for an advantageous modeling of random elds. This thesis is composed of four signi cant contributions in the development and applications of new covariance models for stationary multivariate spatial processes, and nonstationary spatial and spatio-temporal processes. The rst focus of the thesis is on modeling of stationary multivariate spatial random elds through exible multivariate covariance functions. Chapter 2 proposes a semiparametric approach for multivariate covariance function estimation with exible speci cation of the cross-covariance functions via their spectral representations. The proposed method is applied to model and predict the bivariate data of particulate matter concentration (PM2:5) and wind speed (WS) in the United States. Chapter 3 introduces a parametric class of multivariate covariance functions with asymmetric cross-covariance functions. The proposed covariance model is applied to analyze the asymmetry and perform prediction in a trivariate data of PM2:5, WS and relative humidity (RH) in the United States. The second focus of the thesis is on nonstationary spatial and spatio-temporal random elds. Chapter 4 presents a space deformation method which imparts nonstationarity to any stationary covariance function. The proposed method utilizes the functional data registration algorithm and classical multidimensional scaling to estimate the spatial deformation. The application of the proposed method is demonstrated on a precipitation data. Finally, chapter 5 proposes a parametric class of time-varying spatio-temporal covariance functions, which are nonstationary in time. The proposed class is a time-varying generalization of an existing nonseparable stationary class of spatio-temporal covariance functions. The proposed time-varying model is then used to study the seasonality e ect and perform space-time predictions in the daily PM2:5 data from Oregon, United States.
Computational Wavefront Sensing: Theory, Practice, and Applications(2021-06) [Dissertation]
Advisor: Heidrich, Wolfgang
Committee members: Heidrich, Wolfgang; 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 Sen- sor, 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 hard- ware deconvolution approach is demonstrated for computational cameras via a high resolu- tion 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 engineer- ing 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 chal- lenging applications in optical design and metrology.
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.
Control of the CDC48A segregase by the plant UBX-containing (PUX) protein family(2021-05) [Thesis]
Advisor: Arold, Stefan T.
Committee members: Blilou, Ikram; Jaremko, LukaszIn plants, AAA-adenosine triphosphatase (ATPase) Cell Division Control Protein 48 (CDC48) uses the force generated through ATP hydrolysis to pull, extract, and unfold ubiquitylated or sumoylated proteins from the membrane, chromatin, or protein complexes. The resulting changes in protein or RNA content are an important means for plants to control protein homeostasis and thereby adapt to shifting environmental conditions. The activity and targeting of CDC48 are controlled by adaptor proteins, of which the plant ubiquitin regulatory X (UBX) domain-containing (PUX) proteins constitute the largest and most versatile family. However, few PUX proteins have been structurally or functionally characterized and how they participate in the substrate processing of CDC48A is not fully understood. Here, we first performed a comparative bioinformatic analysis, in which we found that the PUX proteins can be functionally divided into six types. We used this classification as a guide for our experimental efforts to elucidate how PUX proteins mediate client recognition and delivery for CDC48A-mediated unfolding. As a first step in this experimental analysis, we cloned and expressed a number of PUX protein constructs, we assessed their interaction features, and obtained crystals for several PUX domains. These bioinformatic and experimental results provide a basis for the in-depth structural and functional analysis of how PUX proteins control the CDC48A segregase.
The Effect of Puccinia triticina Isolates on Rphq2- and Rph22- Expressing Golden SusPtrit Transgenic Families(2021-05) [Thesis]
Advisor: Krattinger, Simon G.
Committee members: Blilou, Ikram; Rayapuram, NaganandThe production of cereal crops is essential to secure a future that feeds the continuously growing population. Rust fungi reduce host fitness by feeding on their living tissue and interfere with the global production of crops. Cereal rusts, like Puccinia hordei (the causal agent of barley leaf rust) and Puccinia triticina (the causal agent of wheat leaf rust), have a narrow host range and colonize only one particular species. The most durable type of resistance, non-host resistance (NHR), is the immunity of an entire plant species to all strains of a pathogen species. Exploring the genetics of NHR has proven to be challenging because most interspecific hybrids are infertile. Previously, barley Rphq2 and Rph22, which encode orthologous lectin receptor-like kinases (LecRKs), were transformed into an experimental barley line, Golden SusPtrit, and showed resistance against adapted and non-adapted leaf rust species. We used these transgenic barley lines in the current project to explore the effect of the LecRKs on four wheat leaf rust (P. triticina) isolates. We used the settling tower method to inoculate four isolates of P. triticina on Rphq2 and Rph22 transgenic families. We found that most transgenic families showed an increase in resistance compared to the non-transgenic control 750-E1. By measuring the infection frequency of the infections, we identified that P. triticina isolates 93012 and 95012 had opposite virulence effects on two barley families, Rphq2-E5 and Rph22-E2A. Although the expression levels of Rphq2 and Rph22 followed an induction trend, we did not find significant differences between the isolates. We conclude that resistance mediated by Rphq2 and Rph22 against P. triticina isolates does not involve an isolate-specific component. Thus, we propose investigating differences between rust species to further explore the molecular aspect of non-host resistance.
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.
Optimal policies for battery operation and design via stochastic optimal control of jump diffusions(2021-04-26) [Thesis]
Advisor: Tempone, Raul
Committee members: Boffi, Daniele; Bolin, DavidTo operate a production plant, one requires considerable amounts of power. With a wide range of energy sources, the price of electricity changes rapidly throughout the year, and so does the cost of satisfying the electricity demand. Battery technology allows storing energy while the electric power is lower, saving us from purchasing at higher prices. Thus, adding batteries to run plants can significantly reduce production costs. This thesis proposes a method to determine the optimal battery regime and its maximum capacity, minimizing the production plant's energy expenditures. We use stochastic differential equations to model the dynamics of the system. In this way, our spot price mimics the Uruguayan energy system's historical data: a diffusion process represents the electricity demand and a jump-diffusion process - the spot price. We formulate a corresponding stochastic optimal control problem to determine the battery's optimal operation policy and its optimal storage capacity. To solve our stochastic optimal control problem, we obtain the value function by solving the Hamilton-Jacobi-Bellman partial differential equation associated with the system. We discretize the Hamilton-Jacobi-Bellman partial differential equation using finite differences and a time splitting operator technique, providing a stability analysis. Finally, we solve a one-dimensional minimization problem to determine the battery's optimal capacity.
Depth Estimation Using Adaptive Bins via Global Attention at High Resolution(2021-04-21) [Thesis]
Advisor: Wonka, Peter
Committee members: Hadwiger, Markus; Ghanem, BernardWe address the problem of estimating a high quality dense depth map from a single RGB input image. We start out with a baseline encoder-decoder convolutional neural network architecture and pose the question of how the global processing of information can help improve overall depth estimation. To this end, we propose a transformer-based architecture block that divides the depth range into bins whose center value is estimated adaptively per image. The nal depth values are estimated as linear combinations of the bin centers. We call our new building block AdaBins. Our results show a decisive improvement over the state-of-the-art on several popular depth datasets across all metrics. We also validate the e ectiveness of the proposed block with an ablation study.
Conductive Stretchable and 3D Printable Nanocomposite for e-Skin Applications(2021-04-21) [Thesis]
Advisor: Baran, Derya
Committee members: Lubineau, Gilles; Lanza, MarioElectronic skin (e-skin) materials have gained a wide range of attention due to their multiple applications in different areas, including soft robotics, skin attachable electronics, prosthetics, and health care. These materials are required to emulate tactile perceptions and sense the surrounding environments while maintaining properties such as flexibility and stretchability. Current e-skin fabrication techniques, such as photolithography, screen printing, lamination, and laser reducing, have limitations in terms of costs and manufacturing scalability, which ultimately preventing e-skin widespread usage. In this work, we introduce conductive stretchable 3D printable skin-like nanocomposite material. Our nanocomposite is easily 3D printed, cost-effective, and actively senses physical stimuli, such as strain and pressure, which gave them the potential to be used in prosthetics, skin-attachable electronics, and soft robotics applications. Using the conductive properties of carbon nanofibers, alongside a polymeric matrix based on Smooth-on platinum cured silicone and crosslinked PDMS, we can obtain a flexible and stretchable material that resembles human skin and can conduct electricity. A great advantage in our composite is the ability to tune its mechanical properties to fit the desired application area through varying PDMS's chain lengths and composition ratios in the nanocomposite. Also, the interconnecting network of micrometer-long nanofibers allows the measurement of resistivity changes upon physical stimuli, granting the nanocomposite sensing abilities. Moreover, we explored and optimized 3D printing of the nanocomposite material, which offering simplicity and versatility for fabricating complex 3D structures at lower costs.
Studies of Novel Small Molecule and Polymer blends for Application in Organic Light-Emitting Diodes(2021-04-20) [Thesis]
Advisor: Anthopoulos, Thomas D.
Committee members: Laquai, Frédéric; McCulloch, Iain; Tung, VincentDisplay technology has become a vital and ubiquitous part of our daily life. Undoubtedly, today’s technologically minded society is living in the era of the digital image. After high resolution and efficiency could successfully be realized, the major trends in display technology now aim towards achieving high color purity for natural looking display colors. Organic light-emitting diodes (OLEDs), as one strong contender for high performance displays and lighting, have been undergoing tremendous industrial and commercial development. Despite the great progress, though, there is still space for improvement, especially in the case of blue light emitting devices. Blue OLEDs are always challenging, since they traditionally suffer from low efficiencies and lifetimes. Both, novel materials and device architectures, are driving ongoing developments while still always aiming to lower the overall costs. In a continual effort to search for robust materials for blue devices, small molecules (SMs) and polymers, are shown to be promising candidates. In this thesis is presented the results of the detailed study of photophysical and electroluminescence (EL) properties in the case of thin films based on blends of the conjugated polymer Poly(9,9-di-n-octylfluorenyl-2,7-diyl) (PFO) and the of novel SMs; 4,4'-(anthracene-9,10-diyl)bis(N,N-bis(4-methoxyphenyl)aniline) (TPAA) and 4,4'-(pyrene-1,6-diyl)bis(N,N-bis(4-methoxyphenyl)aniline) (TPAP). Finally, devices based on these systems are optimized step by step as a solution processable emissive layer (EML), for applications in sky blue OLEDs.
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.
Improving the Self-Consistent Field Initial Guess Using a 3D Convolutional Neural Network(2021-04-12) [Thesis]
Advisor: Schwingenschlögl, Udo
Committee members: Laquai, Frédéric; Zhang, Xiangliang; Gao, XinMost ab initio simulation packages based on Density Functional Theory (DFT) use the Superposition of Atomic Densities (SAD) as a starting point of the self-consistent fi eld (SCF) iteration. However, this trial charge density without modeling atomic iterations nonlinearly may lead to a relatively slow or even failed convergence. This thesis proposes a machine learning-based scheme to improve the initial guess. We train a 3-Dimensional Convolutional Neural Network (3D CNN) to map the SAD initial guess to the corresponding converged charge density with simple structures. We show that the 3D CNN-processed charge density reduces the number of required SCF iterations at different unit cell complexity levels.
Laser Based Pre-treatment of Secondary Bonded Composite T-joints for Improved Energy Dissipation(2021-04-06) [Thesis]
Advisor: Lubineau, Gilles
Committee members: Anthopoulos, Thomas D.; Laquai, Frédéric; Wagih, AhmedThis study demonstrates an experimental investigation into the efficacy of a novel surface pre-treatment technique to improve the toughness and energy dissipation of composite CFRP T-joints. This novel technique optimizes CO2 laser irradiations to remove surface contaminations and modify the surface morphology of CFRP T-joint adherents. Pull-off tests were performed on T-joints that experienced peel-ply (PP) treatment and to those that were ablated with 10% (LC) and 30% (LA) laser power respectively. A further developed alternative pattern between LA and LC surface pre-treatment was examined. Two different quasi-isotropic stacking sequences have been studied by having surface fibers aligned in 0° and 45° direction. A series of surface roughness analysis, optical microscopy, SEM, CT scan and pictorial findings have been carried out to characterize the surface morphologies and failure modes prior to and after the failure. The patterning technique promoted non-local damage mechanisms which resulted in large improvements in the toughness and energy dissipation as compared to the other pre-treatment techniques. Up to ~12 times higher energy dissipation compared to peel-ply pre-treated T-joint were achieved with patterned T-joint structures that are stacked with a 0° surface fiber direction.
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.
Computation Offloading and Service Caching in Heterogeneous MEC Wireless Networks(2021-04) [Thesis]
Advisor: Alouini, Mohamed-Slim
Committee members: Shihada, Basem; Kammoun, Abla; Zhang, XiangliangMobile edge computing (MEC) can dramatically promote the compu- tation capability and prolong the lifetime of mobile users by offloading computation- intensive tasks to edge cloud. In this thesis, a spatial-random two-tier heterogeneous network (HetNet) is modelled to feature random node distribution, where the small- cell base stations (SBSs) and the macro base stations (MBSs) are cascaded with resource-limited servers and resource-unlimited servers, respectively. Only a certain type of application services and finite number of offloaded tasks can be cached and processed in the resource-limited edge server. For that setup, we investigate the per- formance of two offloading strategies corresponding to integrated access and backhaul (IAB)-enabled MEC networks and traditional cellular MEC networks. By using tools from stochastic geometry and queuing theory, we derive the average delay for the two different strategies, in order to better understand the influence of IAB on MEC networks. Simulations results are provided to verify the derived expressions and to reveal various system-level insights.
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.
Wireless Network Coding with Intelligent Reflecting Surfaces(2021-04) [Thesis]
Advisor: Alouini, Mohamed-Slim
Committee members: Shihada, Basem; Laleg-Kirati, Taous-Meriem; Kammoun, AblaConventional wireless techniques are becoming inadequate for beyond fifth-generation (5G) networks due to latency and bandwidth considerations. To increase the wireless network throughput and improve wireless communication systems’ error performance, we propose physical layer network coding (PNC) in an Intelligent Reflecting Surface (IRS)-assisted environment. We consider an IRS-aided butterfly network, where we propose an algorithm for obtaining the optimal IRS phases. Also, analytic expressions for the bit error rate (BER) are derived. The numerical results demonstrate that the scheme proposed in this thesis significantly enhances the BER performance. The proposed scheme is compared to traditional network coding without IRS. For instance, at a target BER of 10−3, 28 dB and 0.75 dB signal to noise ratio (SNR) gains are achieved at the relay and destination node of the 32-element IRS-assisted butterfly network model.
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.