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The metallization and interconnection of Si photovoltaic (PV) devices are among some of the most critically important aspects to ensure the PV cells and modules are cost-effective, highly-efficient, and robust through environmental stresses. The aim of this work is to contribute to the development of these innovations to move them

The metallization and interconnection of Si photovoltaic (PV) devices are among some of the most critically important aspects to ensure the PV cells and modules are cost-effective, highly-efficient, and robust through environmental stresses. The aim of this work is to contribute to the development of these innovations to move them closer to commercialization.Shingled PV modules and laser-welded foil-interconnected modules present an alternative to traditional soldered ribbons that can improve module power densities in a cost-effective manner. These two interconnection methods present new technical challenges for the PV industry. This work presents x-ray imaging methods to aid in the process-optimization of the application and curing of the adhesive material used in shingled modules. Further, detailed characterization of laser welds, their adhesion, and their effect on module performances is conducted. A strong correlation is found between the laser-weld adhesion and the modules’ durability through thermocycling. A minimum laser weld adhesion of 0.8 mJ is recommended to ensure a robust interconnection is formed. Detailed characterization and modelling are demonstrated on a 21% efficient double-sided tunnel-oxide passivating contact (DS-TOPCon) cell. This technology uses a novel approach that uses the front-metal grid to etch-away the parasitically-absorbing poly-Si material everywhere except for underneath the grid fingers. The modelling yielded a match to the experimental device within 0.06% absolute of its efficiency. This DS-TOPCon device could be improved to a 23.45%-efficient device by improving the optical performance, n-type contact resistivity, and grid finger aspect ratio. Finally, a modelling approach is explored for simulating Si thermophotovoltaic (TPV) devices. Experimentally fabricated diffused-junction devices are used to validate the optical and electrical aspects of the model. A peak TPV efficiency of 6.8% is predicted for the fabricated devices, but a pathway to 32.5% is explained by reducing the parasitic absorption of the contacts and reducing the wafer thickness. Additionally, the DS-TOPCon technology shows the potential for a 33.7% efficient TPV device.
ContributorsHartweg, Barry (Author) / Holman, Zachary (Thesis advisor) / Chan, Candace (Committee member) / Bertoni, Mariana (Committee member) / Yu, Zhengshan (Committee member) / Arizona State University (Publisher)
Created2023
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Description
In this dissertation, I implement and demonstrate a distributed coherent mesh beamforming system, for wireless communications, that provides increased range, data rate, and robustness to interference. By using one or multiple distributed, locally-coherent meshes as antenna arrays, I develop an approach that realizes a performance improvement, related to the number

In this dissertation, I implement and demonstrate a distributed coherent mesh beamforming system, for wireless communications, that provides increased range, data rate, and robustness to interference. By using one or multiple distributed, locally-coherent meshes as antenna arrays, I develop an approach that realizes a performance improvement, related to the number of mesh elements, in signal-to-noise ratio over a traditional single-antenna to single-antenna link without interference. I further demonstrate that in the presence of interference, the signal-to-interference-plus-noise ratio improvement is significantly greater for a wide range of environments. I also discuss key performance bounds that drive system design decisions as well as techniques for robust distributed adaptive beamformer construction. I develop and implement an over-the-air distributed time and frequency synchronization algorithm to enable distributed coherence on software-defined radios. Finally, I implement the distributed coherent mesh beamforming system over-the-air on a network of software-defined radios and demonstrate both simulated and experimental results both with and without interference that achieve performance approaching the theoretical bounds.
ContributorsHoltom, Jacob (Author) / Bliss, Daniel W (Thesis advisor) / Alkhateeb, Ahmed (Committee member) / Herschfelt, Andrew (Committee member) / Michelusi, Nicolò (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Linear bipolar circuits, designed with bipolar junction transistors (BJTs), are particularly vulnerable to the effects of space radiation. These circuits, which are usually commercial off-the-shelf (COTS) components, typically exhibit Enhanced Low Dose Rate Sensitivity (ELDRS), which is characterized by the enhancement of degradation when parts are exposed to radiation at

Linear bipolar circuits, designed with bipolar junction transistors (BJTs), are particularly vulnerable to the effects of space radiation. These circuits, which are usually commercial off-the-shelf (COTS) components, typically exhibit Enhanced Low Dose Rate Sensitivity (ELDRS), which is characterized by the enhancement of degradation when parts are exposed to radiation at low dose rates as compared to high dose rates. This phenomenon poses significant problems for the qualification of bipolar parts for use in low dose rate environments, such as most Earth orbits. ELDRS in BJTs has been well-documented in ground-based experiments; however, the effects of low dose rate irradiation on bipolar transistors manufactured in an integrated linear process had never been characterized in space - until the ELDRS experiment was launched in June 2019. The ELDRS instrument measures changes in the active collector and base currents in 24 lateral PNP (LPNP) BJTs on eight packaged die (three BJTs per die). Sixteen of the 24 BJTs are gated, while eight are standard, un-gated LPNPs. Device Under Test (DUT) and measurement variables include oxide thickness, passivation layer, packaging conditions, and gate voltage. This thesis reports the results obtained after more than 20 months of space flight in a highly elliptical Earth orbit. These results demonstrate that this category of bipolar devices is susceptible to low dose rate exposures and therefore exhibits the ELDRS effect in an actual space environment. This thesis also assess the impact of packaging variables on radiation response and examines one of the major causes behind radiation degradation, interface traps. An understanding of radiation effects in real space environments is critical for future missions that use these low-cost COTS bipolar technologies, making these results highly relevant for the satellite community.
ContributorsBenedetto, Adalin (Author) / Barnaby, Hugh J (Thesis advisor) / Goodnick, Stephen (Committee member) / Sanchez, Ivan (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Polarization imaging and polarization microscopy is of great interest in industrial inspection, defense, biomedical and clinical research, food safety, etc. An ideal polarization imaging system suitable for versatile applications should be full-Stokes, compact, broadband, fast, and highly accurate within a large operation angle. However, such a polarization imaging system remains

Polarization imaging and polarization microscopy is of great interest in industrial inspection, defense, biomedical and clinical research, food safety, etc. An ideal polarization imaging system suitable for versatile applications should be full-Stokes, compact, broadband, fast, and highly accurate within a large operation angle. However, such a polarization imaging system remains elusive among state-of-the-art technology. Recently, flat optics based on metasurfaces have been explored for polarization detection and imaging. Compared with state-of-art, metasurface-based solutions have the advantages of compactness, great design flexibility, and feasibility for on-chip integration. This dissertation reports a dual wavelength (630 to 670nm and 480nm to 520nm) chiral metasurfaces featured with sub-wavelength dimension, extinction ratio over 10 across a broad operation bandwidth (175nm) and efficiency over 60%, which can be used for detection and generation of circular polarization (Chapter 2). This dissertation then reports a chip-integrated full-Stokes polarimetric Complementary metal–oxide–semiconductor (CMOS) imaging sensor based on metasurface polarization filter arrays (MPFA) mentioned above. The sensor has high measurement accuracy of polarization states with an angle of view up to 40°. Calibration and characterization of the device are demonstrated, whereby high polarization states measurement accuracy (measurement error <4%) at incidence angle up to ±20° and full Stokes polarization images of polarized objects are shown. (Chapter 3). A scalable fabrication approach based on nano imprint lithography is demonstrated, with improved fabrication efficiency, lower cost, and higher optical performance up to 10 times compared to EBL process. (Chapter 4). Several polarization imaging applications including a dual-camera full-Stokes underwater polarization navigation system are discussed. Polarization mapping under clear sky and clear water is demonstrated for proof concept. Enhancing contrast of objects through turbid water and polarization images of silver dendrites are also discussed (Chapter 5). Though distinctive in its advantages in rich polarization information, most existing Mueller matrix microscope (MMM) operate at single mode, narrow bandwidth with bulky components. This dissertation reports a compact, dual wavelength, dual mode MMM with satisfactory measurement accuracy (Mueller matrix (MM) measurement error≤ 2.1%) using polarimetric imaging sensor mentioned previously, MM imaging of photonic structures, bio-tissues, etc are demonstrated for proof of concept (Chapter 6).
ContributorsZuo, Jiawei (Author) / Yao, Yu (Thesis advisor) / Wang, Chao (Thesis advisor) / Palais, Joseph (Committee member) / Sinha, Kanupriya (Committee member) / Arizona State University (Publisher)
Created2023
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Description
A distributed framework is proposed for addressing resource sharing problems in communications, micro-economics, and various other network systems. The approach uses a hierarchical multi-layer decomposition for network utility maximization. This methodology uses central management and distributed computations to allocate resources, and in dynamic environments, it aims to efficiently respond to

A distributed framework is proposed for addressing resource sharing problems in communications, micro-economics, and various other network systems. The approach uses a hierarchical multi-layer decomposition for network utility maximization. This methodology uses central management and distributed computations to allocate resources, and in dynamic environments, it aims to efficiently respond to network changes. The main contributions include a comprehensive description of an exemplary unifying optimization framework to share resources across different operators and platforms, and a detailed analysis of the generalized methods under the assumption that the network changes are on the same time-scale as the convergence time of the algorithms employed for local computations.Assuming strong concavity and smoothness of the objective functions, and under some stability conditions for each layer, convergence rates and optimality bounds are presented. The effectiveness of the framework is demonstrated through numerical examples. Furthermore, a novel Federated Edge Network Utility Maximization (FEdg-NUM) architecture is proposed for solving large-scale distributed network utility maximization problems in a fully decentralized way. In FEdg-NUM, clients with private utilities communicate with a peer-to-peer network of edge servers. Convergence properties are examined both through analysis and numerical simulations, and potential applications are highlighted. Finally, problems in a complex stochastic dynamic environment, specifically motivated by resource sharing during disasters occurring in multiple areas, are studied. In a hierarchical management scenario, a method of applying a primal-dual algorithm in higher-layer along with deep reinforcement learning algorithms in localities is presented. Analytical details as well as case studies such as pandemic and wildfire response are provided.
ContributorsKarakoc, Nurullah (Author) / Scaglione, Anna (Thesis advisor) / Reisslein, Martin (Thesis advisor) / Nedich, Angelia (Committee member) / Michelusi, Nicolò (Committee member) / Arizona State University (Publisher)
Created2023
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Description
With proliferation of distributed energy resources (DERs) and advent of advanced measurement devices in modern distribution grids, an advanced distribution management system (ADMS) is needed to be developed in order to maintain reliability and efficiency of modern distribution systems. However, the numbers of sensors and measurement devices in distribution networks

With proliferation of distributed energy resources (DERs) and advent of advanced measurement devices in modern distribution grids, an advanced distribution management system (ADMS) is needed to be developed in order to maintain reliability and efficiency of modern distribution systems. However, the numbers of sensors and measurement devices in distribution networks are limited, and communication links between switch devices, sensors, and ADMS are not well-established. Moreover, the fast voltage fluctuation and violation issues caused by high penetration levels of DERs cannot be easily coped with traditional Volt-VAr control (VVC) devices. In this regard, this Dissertation report proposes an ADMS tool including all core components, i.e., topology processor, state estimation, outage detection, DERs scheduling, and Volt-VAr optimization of DERs, for smart distribution networks with DERs, smart meters, and micro-phasor measurement units (micro-PMUs). In order to execute the ADMS tool’s components in an unbalanced distribution system, novel nonlinear and convex AC optimal power flow models based on current-voltage (IVACOPF) formulation are proposed for an unbalanced distribution system with DERs. Applications of the proposed convex IVACOPF model on key parts of ADMS and DERs management system (DERMS), i.e., (i) simultaneous state estimation, topology processor, and outage detection, (ii) DERs scheduling, and (iii) Volt-VAr optimization of DERs, are presented in this report. In this regard, an efficient MIQP-based optimization model based on IVACOPF is proposed to simultaneously identify real-time network topology, estimate system state, and detect outages of unbalanced distribution systems. The proposed model copes with challenges of a real distribution network including: (1) limited locations of measurement devices and unsynchronized measurement data as well as missing and bad data, and (2) complicated mixed-phase switch actions and mutual impedances and shunt admittances. For the Volt-VAr optimization component of ADMS and DERs scheduling, an operational scheduling model of DERs and PV smart inverters with Volt-VAr controllers is proposed using IVACOPF in an unbalanced distribution network. The setpoints of controller setting of each individual PV smart inverter are optimized within the allowable range of the IEEE 1547-2018 standard to improve local as well as system-level voltage regulation in an unbalanced distribution system.
ContributorsSoltani, Zahra (Author) / Khorsand, Mojdeh MKH (Thesis advisor) / Vittal, Vijay VV (Committee member) / Ayyanar, Raja RA (Committee member) / Weng, Yang YW (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Antenna arrays are widely used in wireless communication, radar, remote sensing, and other fields. Compared to traditional linear antenna arrays, novel nonlinear antenna arrays have fascinating advantages in terms of structural simplicity, lower cost, wider bandwidth, faster scanning speed, and lower side-lobe levels. This dissertation explores a novel design of

Antenna arrays are widely used in wireless communication, radar, remote sensing, and other fields. Compared to traditional linear antenna arrays, novel nonlinear antenna arrays have fascinating advantages in terms of structural simplicity, lower cost, wider bandwidth, faster scanning speed, and lower side-lobe levels. This dissertation explores a novel design of a phased array antenna with an augmented scanning range, aiming to establish a clear connection between mathematical principles and practical circuitry. To achieve this goal, the Van der Pol (VDP) model is applied to a single-transistor oscillator to obtain the isolated limit cycle. The coupled oscillators are then integrated into a 1 times 7 coupled phased array, using the Keysight PathWave Advanced Design System (ADS) for tuning and optimization. The VDP model is used for analytic study of bifurcation, quasi-sinusoidal oscillation, quasi-periodic chaos, and oscillator death, while ADS schematics guide engineering implementation and physical fabrication. The coupled oscillators drive cavity-backed antennas, forming a one-dimensional scanning antenna array of 1 times 7. The approaches for increasing the scanning range performance are discussed.
ContributorsZhang, Kaiyue (Author) / Pan, George (Thesis advisor) / Yu, Hongbin (Committee member) / Aberle, James (Committee member) / Palais, Joseph (Committee member) / Arizona State University (Publisher)
Created2023
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Description
The silicon-based solar cell has been extensively deployed in photovoltaic industry and plays an important role in renewable energy industries. A more energy-efficient, environment-harmless and eco-friendly silicon production technique is required for price-competitive solar energy harvesting. Silicon electrorefining in molten salt is promising for the ultrapure solar-grade Si production. To

The silicon-based solar cell has been extensively deployed in photovoltaic industry and plays an important role in renewable energy industries. A more energy-efficient, environment-harmless and eco-friendly silicon production technique is required for price-competitive solar energy harvesting. Silicon electrorefining in molten salt is promising for the ultrapure solar-grade Si production. To avoid using highly corrosive fluoride salt, CaCl2-based salt is widely employed for silicon electroreduction. For Si electroreduction in CaCl2-based salt, CaO is usually added to enhance the solubility of SiO2. However, the existence of oxygen in molten salt could result in system corrosion, anode passivation and the co-deposition of secondary phases such as CaSiO3 and SiO2 at the cathode. This research focuses on the development of reusable oxygen-free CaCl2-based molten salt for solar-grade silicon electrorefining. A new multi-potential electropurification process has been proposed and proven to be more effective in impurities removal. The as-received salt and the salt after electrorefining have been electropurified. The inductively-coupled plasma mass spectrometry and cyclic voltammetry have been utilized to determine the impurities removal of electropurification. The salt after silicon electrorefining has been regenerated to its original purity level before by the multi-potential electropurification process, demonstrating the feasibility of a reusable salt by electropurification. In an oxygen-free CaCl2-based salt without silicon precursor, the silicon dissolved from the silicon anode can be successfully deposited at the cathode. The silicon anode has been operated for more than 50 hours without passivation in the oxygen-free system. Silicon ions start to be deposited after 0.17 g of silicon has been dissolved into the salt from the silicon anode. A 180 µm deposit with a silver-luster surface was obtained at the cathode. The main impurities in the silicon anode such as aluminum, iron and titanium were not found in the silicon deposits. No oxygen-containing secondary phases are detected in the silicon deposits. These results confirm the feasibility of silicon electrorefining in the oxygen-free CaCl2-based salt.
ContributorsTseng, Mao-Feng (Author) / Tao, Meng (Thesis advisor) / Kannan, Arunachala Mada (Committee member) / Mu, Linqin (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2023
Description
ABSTRACT With the fast development of industry, it brings indelible pollution to the natural environment. As a consequence, the air quality is getting worse which will seriously affect people's health. With such concern, continuous air quality monitoring and prediction are necessary. Traditional air quality monitoring methods cannot use

ABSTRACT With the fast development of industry, it brings indelible pollution to the natural environment. As a consequence, the air quality is getting worse which will seriously affect people's health. With such concern, continuous air quality monitoring and prediction are necessary. Traditional air quality monitoring methods cannot use large amount of historical data to make accurate predic-tions. Moreover, the traditional prediction method can only roughly predict the air quality level in a short time. With the development of artificial intelligence al-gorithms [1] and high performance computing, the latest mathematical methods and algorithms are able to generate much more accurate predictions based on long term past data. In this master thesis project, it explore to develop deep learning based air quality prediction based on real sensor network time series air quality data from STAIR system [3].
ContributorsZhou, Zeming (Author) / Fan, Deliang (Thesis advisor) / Cao, Yu (Committee member) / Yu, Haofei (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Artificial Intelligence (AI) and Machine Learning (ML) techniques have come a long way since their inception and have been used to build intelligent systems for a wide range of applications in everyday life. However they are very computationintensive and require transfer of large volume of data from memory to the

Artificial Intelligence (AI) and Machine Learning (ML) techniques have come a long way since their inception and have been used to build intelligent systems for a wide range of applications in everyday life. However they are very computationintensive and require transfer of large volume of data from memory to the computation units. This memory access time constitute significant part of the computational latency and a performance bottleneck. To address this limitation and the ever-growing demand for implementation in hand-held and edge-devices, In-memory computing (IMC) based AI/ML hardware accelerators have emerged. First, the dissertation presents an IMC static random access memory (SRAM) based hardware modeling and optimization framework. A unified systematic study closely models the IMC hardware, and investigates how a number of design variables and non-idealities (e.g. device mismatch and ADC quantization) affect the Deep Neural Network (DNN) accuracy of the IMC design. The framework allows co-optimized selection of different design variables accounting for sources of noise in IMC hardware and robust implementation of a high accuracy DNN. Next, it presents a kNN hardware accelerator in 65nm Complementary Metal-Oxide-Semiconductor (CMOS) technology. The accelerator combines an IMC SRAM that is developed for binarized deep neural networks and other digital hardware that performs top-k sorting. The simulated k Nearest Neighbor accelerator design processes up to 17.9 million query vectors per second while consuming 11.8 mW, demonstrating >4.8× energy-efficiency improvement over prior works. This dissertation also presents a novel floating-point precision IMC (FP-IMC) macro with a hybrid architecture that configurably supports two Floating Point (FP) precisions. Implementing FP precision MAC has been a challenge owing to its complexity. The design is implemented on 28nm CMOS, and taped-out on chip demonstrating 12.1 TFLOPS/W and 66.1 TFLOPS/W for 8-bit Floating Point (FP8) and Block Floating point (BF8) respectively. Finally, another iteration of the FP design is presented that is modeled to support multiple precision modes from FP8 up to FP32. Two approaches to the architectural design were compared illustrating the throughput-area overhead trade-off. The simulated design shows a 2.1 × normalized energy-efficiency compared to the on-chip implementation of the FP-IMC.
ContributorsSaikia, Jyotishman (Author) / Seo, Jae-Sun (Thesis advisor) / Chakrabarti, Chaitali (Thesis advisor) / Fan, Deliang (Committee member) / Cao, Yu (Committee member) / Arizona State University (Publisher)
Created2023