On the Statistical Modeling of the Underwater Optical Wireless Channel Subject to Air Bubbles(2019-05-08) [Thesis]
Advisor: Alouini, Mohamed-Slim
Committee members: Parsani, Matteo; Park, Ki-HongIn underwater wireless optical communications (UWOC), the obstruction of light propagation by air bubbles is one of the main factors which causes light power to fluctuate at the receiver. In this thesis, we construct a statistical model for the received power in the presence of air bubbles. First, we postulate some random variables based on some real experiments, such as the size of a bubble, the generation of each bubble, and the horizontal and vertical movements of a bubble. Second, we mathematically express the amount of obstructed power which the shade of each bubble causes over the beam area and sum them all up to get the total obstructed power. In order to use the method of moments, we find the expectation, the second and/or the third moments of the total obstructed power. Lastly, we use these two or three moments of it to find suitable distributions that match the simulation data, which are the Weibull distribution and Generalized gamma distribution respectively. With these distributions, we construct the statistical model of the received power. Furthermore, we show that those distributions fit well to the simulation data.
A Full Multigrid-Multilevel Quasi-Monte Carlo Approach for Elliptic PDE with Random Coefficients(2019-05-05) [Thesis]
Advisor: Sun, Shuyu
Committee members: Hoteit, Ibrahim; Tempone, Raul; Liu, HailiangThe subsurface flow is usually subject to uncertain porous media structures. However, in most cases we only have partial knowledge about the porous media properties. A common approach is to model the uncertain parameters as random fields, then the expectation of Quantity of Interest(QoI) can be evaluated by the Monte Carlo method. In this study, we develop a full multigrid-multilevel Monte Carlo (FMG-MLMC) method to speed up the evaluation of random parameters effects on single-phase porous flows. In general, MLMC method applies a series of discretization with increasing resolution and computes the QoI on each of them, the success of which lies in the effective variance reduction. We exploit the similar hierarchies of MLMC and multigrid methods, and obtain the solution on coarse mesh Qcl as a byproduct of the multigrid solution on fine mesh Qfl on each level l. In the cases considered in this thesis, the computational saving is 20% theoretically. In addition, a comparison of Monte Carlo and Quasi-Monte Carlo (QMC) methods reveals a smaller estimator variance and faster convergence rate of the latter method in this study.
Robust Estimation of Scatter Matrix, Random Matrix Theory and an Application to Spectrum Sensing(2019-05-05) [Thesis]
Advisor: Alouini, Mohamed-Slim
Committee members: Rue, Haavard; Kammoun, AblaThe covariance estimation is one of the most critical tasks in multivariate statistical analysis. In many applications, reliable estimation of the covariance matrix, or scatter matrix in general, is required. The performance of the classical maximum likelihood method relies a great deal on the validity of the model assumption. Since the assumptions are often approximately correct, many robust statistical methods have been proposed to be robust against the deviation from the model assumptions. M-estimator is an important class of robust estimator of the scatter matrix. The properties of these robust estimators under high dimensional setting, which means the number of dimensions has the same order of magnitude as the number of observations, is desirable. To study these, random matrix theory is a very important tool. With high dimensional properties of robust estimators, we introduced a new method for blind spectrum sensing in cognitive radio networks.
Modular Autonomous Taxiing Simulation and 3D Siamese Vehicle Tracking(2019-05) [Thesis]
Advisor: Ghanem, Bernard
Committee members: Al-Naffouri, Tareq Y.; Thabet, Ali KassemThe automation of navigation for different kinds of vehicles is a research problem of great interest. This problem has applications with unmanned aerial vehicles (UAVs) as well as manned vehicles such as cars and planes. The goal of an autonomous vehicle is to navigate safely from one point to another given a set of high-level instructions and data from a set of sensors. This thesis explores an implementation of a modular approach for autonomously driving taxiing planes before proposing methods for object tracking using a LIDAR sensor which can be incorporated into the autonomous driving pipeline. The taxiing algorithm regresses waypoints for the plane to follow given a high-level driving goal such as ”turn left” or ”go straight”, along with RGB images taken from the cockpit and wings. Waypoints are then used with a separate control system to taxi the plane. The training and testing of this autonomous aircraft is done in a photo-realistic simulator which has been adapted for this task. The policy developed in this fashion is capable of learning how to go straight and how to turn. However, the driving policy is not trained to react to other moving objects. To address this issue, and due to the superior reliability of LIDAR over RGB sensors, an object tracking method using only LIDAR point clouds is proposed. The proposed method uses a novel 3D Siamese network to obtain a similarity score between a model and candidate object point clouds. This similarity score is shown to work for tracking by applying it using an exhaustive search and obtaining improved performances when compared with simple baselines. For a realistic application, the similarity score is applied using candidates provided by a search on the BEV projection of the LIDAR point cloud. This method is shown to provide improved tracking results over other search strategies when using a lower number of candidates.
Gain Enhancement Techniques for mm-wave On-chip Antenna on Lossy CMOS Platforms(2019-05) [Thesis]
Advisor: Shamim, Atif
Committee members: Bagci, Hakan; Wu, YingRecently, there is great interest in achieving higher-level integration, higher data rates, and reduced overall costs. At millimeter-wave (mm-wave) bands, the wavelength is small enough to realize an antenna-on-chip (AoC), which is an ideal solution for high compactness and lower costs. However, the main drawback of AoC is the low resistivity (10 Ω-cm) Si substrate used in the standard CMOS technology, which absorbs most radio-frequency (RF) power that was supposed to be radiated by the on-chip antenna. Moreover, due to the high relative permittivity (11.9) and relatively large electrical thickness of the Si, higher order surface wave modes get excited, which further degrade the antenna radiation performance. In order to alleviate the above-mentioned issues with the low gain of AoC, a combination of an artificial magnetic conductor (AMC) surface, a high dielectric constant superstrate, and a Fresnel lens is presented in this work. The AMC is realized in standard CMOS technology along with the AoC, whereas the superstrate and lens are part of a smart packaging solution. The AMC surface can change wave propagation characteristics at the operating frequency to achieve in-phase reflection, resulting in gain enhancement by reducing the loss in the substrate. The high dielectric constant superstrate behaves as an impedance transformer between the Si substrate and air, thus enhancing the coupling to air. Finally, the Fresnel lens enhances the gain by focusing the electromagnetic (EM) radiation beam at the boresight. For AoC realization, a standard 0.18 μm CMOS process was utilized. A coplanar waveguide (CPW) fed monopole on-chip antenna at 71 GHz, along with the corresponding driving circuit, was designed and fabricated. The AMC enhances the gain by 3 dB. Since the chip needs to be packaged anyways, in this work, we optimize the package to provide further gain enhancement. This smart package, comprising a superstrate and a Fresnel lens, provides a gain enhancement of 16 dB. The overall combination of the optimized AMC surface, superstrate layer, and lens package can provide a gain enhancement of around 19 dB. Furthermore, the package has been realized through additive manufacturing techniques that ensure lower costs for the overall system.
Model Predictive Control and State Estimation for Membrane-based Water Systems(2019-05) [Thesis]
Advisor: Laleg-Kirati, Taous-Meriem
Committee members: Shamma, Jeff S.; Hong, Pei-YingLack of clean fresh water is one of the most pervasive problems afflicting people throughout the world. Efficient desalination of sea and brackish water and safe reuse of wastewater become an insistent need. However, such techniques are energy intensive, and thus, a good control design is needed to increase the process efficiency and maintain water production costs at an acceptable level. This thesis proposes solutions to the above challenges and in particular will be focused on two membranebased water systems: Membrane Distillation (MD) and Membrane Bioreactor (MBR) for wastewater treatment plant (WWPT). The first part of this thesis, Direct Contact Membrane Distillation (DCMD) will study as an example an MD process. MD is an emerging sustainable desalination technique which can be powered by renewable energy. Its main drawback is the low water production rate. However, it can be improved by utilizing advanced control strategies. DCMD is modeled by a set of Differential Algebraic Equations (DAEs). In order to improve its water production, an optimization-based control scheme termed Model Predictive Control (MPC) provides a natural framework to optimally operate DCMD processes due to its unique control advantages. Among these advantages are the flexibility provided in formulating the objective function, the capability to directly handle process constraints, and the ability to work with various classes of nonlinear systems. Motivated by the above considerations, two MPC schemes that can maximize the water production rate of DCMD systems have been developed. The first MPC scheme is formulated to track an optimal set-point while taking input and stability constraints into account. The second MPC scheme, Economic MPC (EMPC), is formulated to maximize the distilled water flux while meeting input, stability and other process operational constraints. The total water production under both control designs is compared to illustrate the effectiveness of the two proposed control paradigms. Simulation results show that the DCMD process produces more distilled water when it is operated by EMPC than when it is operated by MPC. The above control techniques assume the full access to the system states. However, this is not the case for the DCMD plant. To effectively control the closed-loop system, an observer design that can estimate the values of the unmeasurable states is required. Motivated by that, a nonlinear observer design for DCMD is proposed. In addition, the effect of the estimation gain matrix on the differentiation index of the DAE system is investigated. Numerical simulations are presented to illustrate the effectiveness of the proposed observer design. The observer-based MPC and EMPC are also studied in this work. Mathematical modeling of a wastewater treatment system is critical because it enhances the process understanding and can be used for process design and process optimization. Motivated by the above considerations, modeling and optimal control strategies have been developed and applied to the MBR-based wastewater treatment process. The model is an extension of the well-known Benchmark simulation models for wastewater treatment. In addition, model predictive control has been applied to maintain the dissolved oxygen concentration level at the desired value. In addition, a conventional PID controller has also been developed. The simulation results show that the both of controllers can be used for dissolved oxygen concentration control. However, MPC has better performance compared to PID scenario.
Expandable Polymer Assisted Wearable Personalized Medicinal Platform(2019-05) [Thesis]
Advisor: Hussain, Muhammad Mustafa
Committee members: Alouini, Mohamed-Slim; Schwingenschlögl, UdoConventional healthcare and the practice of medicine largely relies on the ineffective concept of one size fits all. Personalized medicine is an emerging therapeutic approach that aims to develop an advanced therapeutic technique that provides tailor-made therapy based on every individuals’ needs by delivering the right drug at the right time with the right amount of dosage. The advancement in technologies such as flexible electronics, microfluidics, biosensors, and advanced artificial intelligence can enable the realization of a truly effective personalized therapy. However, currently, there is a lack for a personalized minimally-invasive wearable closed-loop drug delivery system that is continuous, automated, conformal to the skin and cost-effective. Thus, this thesis focuses on the design, fabrication, optimization, and application of an automated personalized microfluidics drug delivery platform augmented with flexible biosensors, heaters, and expandable polymeric actuator. The platform provides precise drug delivery with spatiotemporal control over the administered dose as a response to real-time physiological changes of the individual. The system is flexible enough to be conformal to the skin and drug is transdermally administered through biocompatible microneedles. The platform includes a flexible multi-reservoir microfluidics layer, flexible and conformal heating elements, skin sensors and processing units which are powered by a lightweight battery integrated into the platform. The developed platform was fabricated using rapid, cost-effective techniques that are independent of advanced microfabrication facilities to expand its applications to low-resource setting and environments.
Resource Allocation in Future Terahertz Networks(2019-05) [Thesis]
Advisor: Alouini, Mohamed-Slim
Committee members: Shihada, Basem; Amin, OsamaTerahertz (THz) band represents the unused frequency band between the microwave and optical bands and lies in the range of frequencies between 0.1 to 10 THz. As a result, the THz signal generation can be done using electronic or photonic circuits. Moreover, the channel gain has hybrid features from both microwave and optical bands allowing to reap the benefits of each band. Adopting such a technology can mitigate the spectrum scarcity and introduce a substantial solution to other systems such as visible light communications. Despite of the generous bandwidth, the THz communications suffer from high attenuation that increases with adopted frequency similar to the microwave frequency band. Furthermore, THz communications are subject to a different type of attenuation called Molecular Absorption, that depends on the chemical nature of the ambiance air. Thus, THz transmitters need to use extra power and high antenna gains to overcome signal loss and compensate the short distance range limitation. In this thesis, we investigate the pathloss model to compute the overall attenuation faced by the THz wave for different frequencies and weather conditions. Then, we use the THz technology to support the operation of uplink networks using directional narrow beams. We optimize the uplink communication network resource represented in the frequency bands and the assigned power in order to minimize the total power consumption while achieving a specific quality of service. Furthermore, we investigate the impact of weather conditions and the system’s requirements in order to guarantee a better performance.
Towards Multistate Magnetic Tunnel Junctions for Memory and Logic Applications(2019-05) [Thesis]
Advisor: Fariborzi, Hossein
Committee members: Shamim, Atif; Kosel, JürgenFor many decades, the revolution in semiconductor industry has continuously been powered by the successful down scaling of complementary metal-oxide semiconductor (CMOS) technology to produce integrated circuits with improved performance at lower cost. However, current charge-based CMOS technology is already approaching physical limits and, thus, encounters a number of technological challenges. Spintronics is an emerging and rapidly evolving research field that has a great potential to overcome these challenges confronting CMOS by introducing the electron spin, in addition to electron charge, as an extra degree of freedom. Traditional spintronic devices are based on the alignment of spins in magnetic layers, manipulated by spin-polarized currents. Thus, employing the non-volatile nature of layer magnetization and its direction to represent the bit state, spintronics provides power-efficient devices that are attractive for memory and logic applications. Magnetoresistive random access memory (MRAM) is one of the most essential applications of spin based electronics, which has already been recognized as the leading candidate for future universal memory. MRAM cells use spin-based magnetic tunnel junctions (MTJs) as the fundamental storage blocks. These conventional MTJs employ the use of magnetic elements with a single axis of magnetization, which provide two resistance states, capable of storing one bit of information. Enhancing the memory density is one of the major challenges encountered by MRAM industry, as the straightforward approach of reducing the magnetic bit size is unfeasible with magnetic devices due to intrinsic superparamagnetism effects. In this thesis, we propose increasing the bit density in MRAM by implementing shape anisotropy induced multistate MTJs. By patterning the free ferromagnetic layer of MTJs in the shape of four intersecting ellipses we achieve four in-plane stable axes of magnetization, capable of providing eight resistance states in total, the switching between which is performed by spin-orbit torques (SOT) in spin Hall metals (SHM). We initially verify the proposed concept with micromagnetic simulations followed by fabrication and, consequent, room temperature characterization of the first experimental prototypes.
Optimization of Process Variables for Oxidative Coupling of Methane(2019-05) [Thesis]
Advisor: Sarathy, Mani
Committee members: Gascon, Jorge; Farooq, AamirOxidative coupling of methane (OCM) is a promising route for converting abundant natural gas resources into more useful chemicals like paraffins and olefins (primarily C2). However, to date, there is no current OCM production plant due to low overall conversion and selectivity to the desired product(s). In this work, different operating factors are studied experimentally and through simulation with respect mainly to three responses: CH4 conversion, C2 main product selectivity, and COx side product selectivity. The aim is to identify the best operating condition for maximum ethylene production combined with COx production. Design of experiments (DoE) method was used to analyze the experimental results by applying the full factorial approach. Simulation results were studied by finding the correlation strength between input factors and responses. It was found that the performance of an OCM reactor could be greatly improved under optimal operating conditions. Operating temperature and CH4/O2 ratio have the highest influence while catalyst weight and flow rate have the lowest influence on the OCM responses and mainly depend on rector dimensions.
Structural Analysis of Arabidopsis thaliana CDC48A ATPase using Single Particle Cryo-Electron Microscopy(2019-05) [Thesis]
Advisor: Arold, Stefan T.
Committee members: Jaremko, Łukasz; Gao, XinCdc48A and its human homologue P97 are from ATPase family, which play a variety of roles in cellular activates and it has a crucial involvement in protein quality control pathways. It is best known for its involvement in endoplasmic reticulum associated protein degradation (ERAD), where it mediates the degradation of the aggerated or misfolded proteins by the proteasome. Considering the multiple functions of Cdc48A in many protein regulatory processes, it is a potential therapeutic target for neurogenerative diseases and cancer. Cdc48A polypeptide comprises N domain, followed by D1 and D2 domains respectively that are joined by linkers, whereas functionally it forms a homo hexameric complex. Since Cdc48A is from the ATPase family, it uses the ATP hydrolysis to generate a mechanical force with its co-factors to perform its functions. There are many cofactors that interact with Cdc48A and two of them are Ufd1-NpI4 which in turn interact with ubiquitinated proteins from the ER membrane. The mechanism linking the conversion of the energy of ATP hydrolysis into mechanical force and unfolding the substrate is vague. My aim is to reconstruct a first 3D- model of plant Cdc48A using single particle cryo-EM, which serves the basis to conduct more detailed mechanistic studies towards substrate unfolding and threading/unfolding in the future. In general, results showed one defined structure of cdc48A at ~ 9.8 Å, which is the ADP-ATP conformation. Although another other structure was also resolved at ~ 8.9 Å, it was hard to characterize due to its dissimilarity with known structures of Cdc48A homologues and thus requires further characterization.
Seawater-induced Biofouling in Direct Contact Membrane Distillation(2019-05) [Thesis]
Advisor: Ghaffour, NorEddine
Committee members: Saikaly, Pascal; Mahfouz, Magdy M.Membrane distillation (MD) is a promising desalination technology which allows to achieve high salt rejection at low energy expenses as compared to conventional desalination processes. However, just like in any other membrane separation process, the MD membrane is susceptible to biofouling which is one of the critical problems in membrane-based systems. In this study, we investigated the effects of spacer design and feed temperature on the biofilm formation and proliferation in a flat-sheet direct contact membrane distillation (DCMD) used for desalination of the Red Sea water. Two types of spacers (Standard & 1-Hole) were designed to evaluate their efficiency in biofouling mitigation at three different feed water temperatures (47 °C, 55 °C and 65 °C). Our results showed that while 1-hole spacer was more efficient in reducing biofouling at 47 °C (permeate flux declines of 73.2% and 79.6% after 5 days of DCMD process using 1-hole and standard spacers, respectively). Standard spacer over-performed at higher feed water temperatures (65.7%, and 75.2% after 5 days of DCMD process at 55 °C and 65 °C, respectively). The Optical Coherence Tomography (OCT) revealed a significant transition of biofilm morphology with increasing feed water temperature for both types of spacers. While thicker and more porous biofouling structures were formed on the surface of MD membrane at 47 °C and 55 °C, thinner non-porous layer prevailed on the membrane surface at a feed water temperature of 65 °C. This observation was supported by direct enumeration of bacterial cells inside the biofilm by flow cytometry which revealed a significant decrease in the total number of cells when the feed water temperature was increased from 55 °C to 65 °C. Moreover, this process was accompanied by the permeate flux decline and increase of coolant water conductivity regardless of the spacer type. The results of our study have shown high rejection of dissolved organic carbon (DOC > 97%) and absence of bacterial contamination of permeate water which is important due to use of microporous polymeric membrane with 0.5 m pore size. The obtained results indicated the importance of operational conditions in controlling the biofouling in the MD system.
From DNA on beads to proteins in a million droplets(2019-05) [Thesis]
Advisor: Arold, Stefan T.
Committee members: Hamdan, Samir; Mahfouz, Magdy M.Cell-free transcription and translation systems promise to accelerate and simplify the engineering of synthetic proteins, biological circuits or metabolic pathways. Microfluidic droplet platforms can generate millions of reactions in parallel. This allows cell-free reactions to be miniaturized down to picoliter volumes. Nevertheless, the true potential of microfluidics have not been reached for cell-free bioengineering. Better approaches are needed for reaching sufficient in-drop expression levels while efficiently creating DNA diversity among droplets. This work develops a droplet microfluidic platform for single or multiple protein expression from a single DNA coated bead per droplet. This opens up the possibility to diversify a million droplets for synthetic biology applications.
Inkjet Printing of a Two-Dimensional Conductor for Cutaneous Biosignal Monitoring(2019-05) [Thesis]
Advisor: Inal, Sahika
Committee members: Baran, Derya; Arold, Stefan T.Wearables for health monitoring are rapidly advancing as evidenced by the number of wearable products on the market. More recently, the US Food and Drug Administration approved the Apple Watch for heart monitoring, indicating that wearables are going to be a part of our lives sooner than expected. However, wearables are still based on rigid, conventional electronic materials and fabrication procedures. The use of flexible conducting materials fabricated on flexible substrates allows for more comprehensive health monitoring because of the seamless integration and conformability of such devices with the human skin. Many materials can be used to fabricate flexible electronics such as thin metals, liquid metals, conducting polymers, and 1D and 2D materials. Ti3C2 MXene is a promising 2D material that shows flexibility as well as desirable electronic properties. Ti3C2 MXene is easily processable in aqueous solutions and can be an excellent functional ink for inkjet printing. Here we report the fabrication and the properties of Ti3C2 MXene films inkjet-printed from aqueous dispersions with a nonionic surfactant. The films are uniform and formed with only a few layers on glass and tattoo paper. The MXene films printed on tattoo are used to record ECG signals with comparable signal-to-noise ratio to commercial Ag/AgCl electrodes despite the absence of gels to lower skin-contact impedance. Due to their high charge storage capacity and mixed (ionic and electronic) conductivity, inkjet-printed MXene films open up a new avenue for applications beyond health monitoring.
Privacy Concerned D2D-Assisted Delay-Tolerant Content Distribution System(2019-04-28) [Thesis]
Advisor: Shihada, Basem
Committee members: Alouini, Mohamed-Slim; Amin, OsamaIt is foreseeable that device-to-device (D2D) communication will become a standard feature in the future, for the reason that it offloads the data traffic from network infrastructures to user devices. Recent researches prove that delivering delay-tolerant contents through content delivery network (CDN) by D2D helps network operators increase spectral and energy efficiency. However, protecting the private information of mobile users in D2D assistant CDN is the primary concern, which directly affects the willingness of mobile users to share their resources with others. In this thesis, we proposed a privacy concerned top layer system for selecting the sub-optimal set of mobile nodes as initial mobile content provider (MCP) for content delivery in any general D2D communications, which implies that our proposed system does not rely on private user information such as location, affinity, and personal preferences. We model the initial content carrier set problem as an incentive maximization problem to optimize the rewards for network operators and content providers. Then, we utilized the Markov random field (MRF) theory to build a probabilistic graphical model to make an inference on the observation of delivered contents. Furthermore, we proposed a greedy algorithm to solve the non-linear binary integer programming (NLBIP) problem for selecting the optimal initial content carrier set. The evaluations of the proposed system are based on both a simulated dataset and a real-world collected dataset corresponding to the off-line and on-line scenarios.
Theoretical and Experimental Studies of Optical Properties of BAlN and BGaN Alloys(2019-04-21) [Thesis]
Advisor: Li, Xiaohang
Committee members: Schwingenschlögl, Udo; Ooi, Boon S.Wurtzite III-nitride semiconductor materials have many technically important applications in optical and electronic devices. As GaN-based visible light-emitting diodes (LEDs) and lasers starts to mature, interest in developing UV devices starts to rise. The search for materials with larger bandgaps and high refractive index contrast in the UV range has inspired multiple studies of BN-based materials and their alloys with traditional III-nitrides. Additionally, alloying III-nitrides with boron can reduce their lattice parameters giving a new option for strain engineering and lattice matching. In this work I investigate the refractive indices of BAlN and BGaN over the entire compositional range using hybrid density functional theory (DFT). An interesting non-linear trend of the refractive index curves appears as boron content is increased in the BAlN and BGaN alloys. The results of this calculation were interpolated and plotted in three dimensions for better visualization. This interpolation gives a 3D dataset that can be used in designing a myriad of devices at all binary and ternary alloy compositions in the BAlGaN system. The interpolated surface was used to find an optimum design for a strain-free, high reflection coefficient and high bandwidth DBR. The performance of this DBR was quantitatively evaluated using finite element simulations. I found that the maximum DBR reflectivity with widest bandwidth for our materials occurs at a lattice parameter of 3.113 Å using the generated 3D dataset. I use the corresponding material pair to simulate a DBR at the wavelength 375 nm in the UVA range. A design with 25 pairs was found to have a peak reflectivity of 99.8%. This design has a predicted bandwidth of 26 nm measured at 90% peak performance. The high reflectivity and wide bandwidth of this lattice-matched design are optimal for UVA VCSEL applications. I have assisted in exploring different metalorganic chemical vapor deposition (MOCVD) techniques, continuous growth and pulsed-flow modulation, to grow and characterize BAlN alloys. Samples grown using continuous flow show better optical quality and are characterized using spectroscopic ellipsometry. The refractive index of samples obtained experimentally is significantly below the predicted value using DFT.
Poly Silicon on Oxide Contact Silicon Solar Cells(2019-04-17) [Thesis]
Advisor: De Wolf, Stefaan
Committee members: Laquai, Frédéric; Ooi, Boon S.Silicon photovoltaic (PV) is a promising solution for energy shortage and environmental pollution. We are experiencing an era when PV is exponentially increasing. Global cumulative installation had reached 380 GW in 2017. Among which, silicon-based PV productions share more than 90% market. Performance of the first two-generation commercial popular silicon solar cells - Al-BSF and PERC - are limited by metal/Si contacts, where interface defects significantly reduce the open-circuit voltage. In this context, full-area passivation concepts are proposed for c-Si solar cells, with expectation to enhance the efficiency via reducing carrier recombination loss at the contact regions. In this thesis, poly silicon on oxide (POLO) passivating contact is developed for high efficiency c-Si solar cells. We unveiled the working mechanisms of POLO cells and then optimized the device performance based on our conclusion. We use boiling nitric acid to oxidize c-Si surface, which is of significance to determine the POLO working mechanisms. Phosphorus and boron doped silicon films are deposited by plasma enhanced vapor deposition (PECVD) or low-pressure vapor deposition (LPCVD) followed by high temperature (>800°C) annealing. SiOx structural evolution process under different annealing temperature was observed and the corresponding effects on passivation have been elucidated. The carrier transport mechanisms in the POLO contact annealed at high temperature, e.g. 800°C 900°C, were explored. We unveil that carrier transport in POLO structure is a combination of tunneling and pinhole transport, but dominant at varied temperature regions. Phosphorus-doped n-type POLO contact is optimized by several parameters, such as doping concentration, film thickness, annealing temperature, film deposition temperature, film relaxation time during annealing process, etc. We successfully obtained minority carrier lifetime over 10ms and contact resistivity lower than 30 mΩ·cm2. Boron-doped p-type POLO contact is also optimized by changing the doping concentration and annealing temperature. Finally, further hydrogen passivation is applied to enhance p-type POLO contact passivation, achieving an iVoc>690 mV, J0 <5 fA/cm2 and contact resistivity 1.3 mΩ·cm2. With the optimized n-type and p-type POLO contacts, an efficiency over 18% is achieved on n-type c-Si solar cells with a flat front surface.
Power Adaption Over Fluctuating Two-Ray Fading Channels and Fisher-Snedecor F Fading Channels(2019-04) [Thesis]
Advisor: Alouini, Mohamed-Slim
Committee members: Al-Naffouri, Tareq Y.; Park, Ki-HongIn this thesis, we investigate the ergodic capacity under several power adaption schemes, including optimal power and rate algorithm (OPRA), optimal rate algo rithm (ORA), channel inversion (CI), and truncated channel inversion (TCI), over fluctuating two-ray (FTR) fading channels and Fisher-Snedecor F fading channels. After some mathematical manipulations, the exact expressions for the EC under those power adaption schemes are derived. To simplify the expressions and also get some insights from the analysis, the corresponding asymptotic expressions for the EC are also derived in order to show the slope and power offset of the EC in the high signal-to-noise ratio (SNR) region. These two metrics, i.e., slope and power offset, govern the EC behaviour in the high SNR region. Specifically, from the derived asymptotic expressions, we find that the slope of the EC of OPRA and ORA over FTR fading channels is always unity with respect to the average SNR in the log-scale in high SNRs, while the asymptotic EC of the TCI method is not a line function in the log-scale. For the Fisher-Snedecor F fading channel, the slope of asymptotic EC under OPRA, ORA, and CI (m > 1) schemes is unity in the log-scale, where m is the fading parameter. The slope of the TCI method depends on m, i.e., unity for m > 1 and m for m > 1, while the asymptotic EC of TCI is not a line function for m = 1. Finally, Monte-Carlo simulations are used to demonstrate the correctness of the derived expressions.
Wavelength Dependence of Underwater Turbulence Characterized Using Laser-Based White Light(2019-04) [Thesis]
Advisor: Ooi, Boon S.
Committee members: Alouini, Mohamed-Slim; Shihada, Basem; Ng, Tien KheeThe means of communication in oceanic environments is currently dominated by sonar. Although it is reliable for long-distance transmission, the vision of internet of underwater things (IoUT) requires an alternate means for high-data-rate transmission. It is also envisaged that a networked underwater and above-water objects, such as sensor nodes, and autonomous underwater vehicles will benefit seafloor exploration. The use of laser-based optical communication is poised to realize this dream while working hand-in-hand with acoustic and radio-frequency technologies from the littoral zone to deep blue sea. While blue and green lasers are typically utilized depending on the optical properties of the water, laser-based white light is attractive in a number of aspects. In this thesis, we proposed and realized the use of white light to model the channel and to provide the immediate decision for the preferred system configuration, which is critical for developing reliable communication links, particularly, in the presence of turbulence, which makes the alignment of underwater wireless optical communication (UWOC) links challenging. Temperature and salinity changes are among factors that change the refraction index, giving rise to beam wander. This thesis explores the dependence of underwater turbulence on the wavelength. After comparing the performance of red, green, and blue lasers, an ultra-fast comprehensive method that utilizes a white-light source that can produce a wide range of wavelengths is implemented. Experimental results show an 80%-decrease in the scintillation index as the wavelength is increased from 480 to 680 nm in weak turbulence caused by a 0.02-℃/cm temperature gradient with a 40-ppt salt concentration, which emulates conditions found in the Red Sea. The effect of turbulence on the bit error ratio (BER) is also investigated experimentally. Temperature gradients increased the BER especially for shorter wavelengths. The results along long-transmission distances were verified using Monte Carlo simulations. The correlation matrix between wavelengths was studied, which is important for designing multiple-input multiple-output systems. The results obtained show that as the difference in the wavelengths increases, the correlation decreases. Based on the interplay among scintillations, scattering, absorption, and the correlation between different wavelengths, it is possible to design a more reliable UWOC link.
Object Detection Using Multiple Level Annotations(2019-04) [Thesis]
Advisor: Ghanem, Bernard
Committee members: Al-Naffouri, Tareq Y.; Thabet, Ali KassemObject detection is a fundamental problem in computer vision. Impressive results have been achieved on large-scale detection benchmarks by fully-supervised object detection (FSOD) methods. However, FSOD approaches require tremendous instance-level annotations, which are time-consuming to collect. In contrast, weakly supervised object detection (WSOD) exploits easily-collected image-level labels while it suffers from relatively inferior detection performance. This thesis studies hybrid learning methods on the object detection problems. We intend to train an object detector from a dataset where both instance-level and image-level labels are employed. Extensive experiments on the challenging PASCAL VOC 2007 and 2012 benchmarks strongly demonstrate the effectiveness of our method, which gives a trade-off between collecting fewer annotations and building a more accurate object detector. Our method is also a strong baseline bridging the wide gap between FSOD and WSOD performances. Based on the hybrid learning framework, we further study the problem of object detection from a novel perspective in which the annotation budget constraints are taken into consideration. When provided with a fixed budget, we propose a strategy for building a diverse and informative dataset that can be used to optimally train a robust detector. We investigate both optimization and learning-based methods to sample which images to annotate and which level of annotations (strongly or weakly supervised) to annotate them with. By combining an optimal image/annotation selection scheme with the hybrid supervised learning, we show that one can achieve the performance of a strongly supervised detector on PASCAL-VOC 2007 while saving 12:8% of its original annotation budget. Furthermore, when 100% of the budget is used, it surpasses this performance by 2:0 mAP percentage points.