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Description
This dissertation details a study of wide-bandgap molecular beam epitaxy (MBE)-grown single-crystal MgxCd1-xTe. The motivation for this study is to open a pathway to reduced $/W solar power generation through the development of a high-efficiency 1.7-eV II-VI top cell current-matched to low-cost 1.1-eV silicon. This paper reports the demonstration of monocrystalline 1.7-eV MgxCd1-xTe/MgyCd1-yTe (y>x) double heterostructures (DHs) with a record carrier lifetime of 560 nanoseconds, along with a 1.7-eV MgxCd1-xTe/MgyCd1-yTe (y>x) single-junction solar cell with a record active-area efficiency of 15.2% and a record open-circuit voltage (VOC) of 1.176 V. A study of indium-doped n-type 1.7-eV MgxCd1-xTe with a carrier activation of up to 5 × 1017 cm-3 is presented with promise to increase device VOC. Finally, this paper reports an epitaxial lift-off (ELO) technology using water-soluble MgTe for the creation of free-standing MBE-grown II-VI single-crystal CdTe and 1.7-eV MgxCd1-xTe solar cells freed from lattice-matched InSb(001) substrates. Photoluminescence (PL) spectroscopy measurements comparing intact and free-standing films reveal the survival of optical quality in CdTe DHs after ELO. This technology opens up several possibilities to drastically increase cell conversion efficiency through improved light management and transferability into monolithic multijunction devices. Lastly, this report will present considerations for future work in each of the study areas mentioned above.
ContributorsCampbell, Calli Michele (Author) / Zhang, Yong-Hang (Thesis advisor) / Chan, Candance K (Committee member) / King, Richard R (Committee member) / Arizona State University (Publisher)
Created2019
Description
Lidar has demonstrated its utility in meteorological studies, wind resource assessment, and wind farm control. More recently, lidar has gained widespread attention for autonomous vehicles.
The first part of the dissertation begins with an application of a coherent Doppler lidar to wind gust characterization for wind farm control. This application focuses on wind gusts on a scale from 100 m to 1000 m. A detecting and tracking algorithm is proposed to extract gusts from a wind field and track their movement. The algorithm was implemented for a three-hour, two-dimensional wind field retrieved from the measurements of a coherent Doppler lidar. The Gaussian distribution of the gust spanwise deviation from the streamline was demonstrated. Size dependency of gust deviations is discussed. A prediction model estimating the impact of gusts with respect to arrival time and the probability of arrival locations is introduced. The prediction model was applied to a virtual wind turbine array, and estimates are given for which wind turbines would be impacted.
The second part of this dissertation describes a Time-of-Flight lidar simulation. The lidar simulation includes a laser source module, a propagation module, a receiver module, and a timing module. A two-dimensional pulse model is introduced in the laser source module. The sampling rate for the pulse model is explored. The propagation module takes accounts of beam divergence, target characteristics, atmosphere, and optics. The receiver module contains models of noise and analog filters in a lidar receiver. The effect of analog filters on the signal behavior was investigated. The timing module includes a Time-to-Digital Converter (TDC) module and an Analog-to-Digital converter (ADC) module. In the TDC module, several walk-error compensation methods for leading-edge detection and multiple timing algorithms were modeled and tested on simulated signals. In the ADC module, a benchmark (BM) timing algorithm is proposed. A Neyman-Pearson (NP) detector was implemented in the time domain and frequency domain (fast Fourier transform (FFT) approach). The FFT approach with frequency-domain zero-paddings improves the timing resolution. The BM algorithm was tested on simulated signals, and the NP detector was evaluated on both simulated signals and measurements from a prototype lidar (Bhaskaran, 2018).
The first part of the dissertation begins with an application of a coherent Doppler lidar to wind gust characterization for wind farm control. This application focuses on wind gusts on a scale from 100 m to 1000 m. A detecting and tracking algorithm is proposed to extract gusts from a wind field and track their movement. The algorithm was implemented for a three-hour, two-dimensional wind field retrieved from the measurements of a coherent Doppler lidar. The Gaussian distribution of the gust spanwise deviation from the streamline was demonstrated. Size dependency of gust deviations is discussed. A prediction model estimating the impact of gusts with respect to arrival time and the probability of arrival locations is introduced. The prediction model was applied to a virtual wind turbine array, and estimates are given for which wind turbines would be impacted.
The second part of this dissertation describes a Time-of-Flight lidar simulation. The lidar simulation includes a laser source module, a propagation module, a receiver module, and a timing module. A two-dimensional pulse model is introduced in the laser source module. The sampling rate for the pulse model is explored. The propagation module takes accounts of beam divergence, target characteristics, atmosphere, and optics. The receiver module contains models of noise and analog filters in a lidar receiver. The effect of analog filters on the signal behavior was investigated. The timing module includes a Time-to-Digital Converter (TDC) module and an Analog-to-Digital converter (ADC) module. In the TDC module, several walk-error compensation methods for leading-edge detection and multiple timing algorithms were modeled and tested on simulated signals. In the ADC module, a benchmark (BM) timing algorithm is proposed. A Neyman-Pearson (NP) detector was implemented in the time domain and frequency domain (fast Fourier transform (FFT) approach). The FFT approach with frequency-domain zero-paddings improves the timing resolution. The BM algorithm was tested on simulated signals, and the NP detector was evaluated on both simulated signals and measurements from a prototype lidar (Bhaskaran, 2018).
ContributorsZhou, Kai (Author) / Calhoun, Ronald (Thesis advisor) / Chen, Kangping (Committee member) / Tang, Wenbo (Committee member) / Peet, Yulia (Committee member) / Krishnamurthy, Raghavendra (Committee member) / Arizona State University (Publisher)
Created2019
How Does Technology Development Influence the Assessment of Parkinson’s Disease? A Systematic Review
Description
Parkinson’s disease (PD) is a neurological disorder with complicated and disabling motor and non-motor symptoms. The pathology for PD is difficult and expensive. Furthermore, it depends on patient diaries and the neurologist’s subjective assessment of clinical scales. Objective, accurate, and continuous patient monitoring have become possible with the advancement in mobile and portable equipment. Consequently, a significant amount of work has been done to explore new cost-effective and subjective assessment methods or PD symptoms. For example, smart technologies, such as wearable sensors and optical motion capturing systems, have been used to analyze the symptoms of a PD patient to assess their disease progression and even to detect signs in their nascent stage for early diagnosis of PD.
This review focuses on the use of modern equipment for PD applications that were developed in the last decade. Four significant fields of research were identified: Assistance diagnosis, Prognosis or Monitoring of Symptoms and their Severity, Predicting Response to Treatment, and Assistance to Therapy or Rehabilitation. This study reviews the papers published between January 2008 and December 2018 in the following four databases: Pubmed Central, Science Direct, IEEE Xplore and MDPI. After removing unrelated articles, ones published in languages other than English, duplicate entries and other articles that did not fulfill the selection criteria, 778 papers were manually investigated and included in this review. A general overview of PD applications, devices used and aspects monitored for PD management is provided in this systematic review.
This review focuses on the use of modern equipment for PD applications that were developed in the last decade. Four significant fields of research were identified: Assistance diagnosis, Prognosis or Monitoring of Symptoms and their Severity, Predicting Response to Treatment, and Assistance to Therapy or Rehabilitation. This study reviews the papers published between January 2008 and December 2018 in the following four databases: Pubmed Central, Science Direct, IEEE Xplore and MDPI. After removing unrelated articles, ones published in languages other than English, duplicate entries and other articles that did not fulfill the selection criteria, 778 papers were manually investigated and included in this review. A general overview of PD applications, devices used and aspects monitored for PD management is provided in this systematic review.
ContributorsDeb, Ranadeep (Author) / Ogras, Umit Y. (Thesis advisor) / Shill, Holly (Committee member) / Chakrabarti, Chaitali (Committee member) / Arizona State University (Publisher)
Created2019
Description
The following report details the motivation, design, analysis, simulation and hardware implementation of a DC/DC converter in EV drivetrain architectures. The primary objective of the project was to improve overall system efficiency in an EV drivetrain. The methodology employed to this end required a variable or flexible DC-Link voltage at the input of the inverter stage. Amongst the several advantages associated with such a system are the independent optimization of the battery stack and the inverter over a wide range of motor operating conditions. The incorporation of a DC/DC converter into the drivetrain helps lower system losses but since it is an additional component, a number of considerations need to be made during its design. These include stringent requirements on power density, converter efficiency and reliability.
These targets for the converter are met through a number of different ways. The switches used are Silicon Carbide FETs. These are wide band gap (WBG) devices that can operate at high frequencies and temperatures. Since they allow for high frequency operation, a switching frequency of 250 khz is proposed and implemented. This helps with power density by reducing the size of passive components. High efficiencies are made possible by using a simple soft switching technique by augmenting the DC/DC converter with an auxiliary branch to enable zero voltage transition.
The efficacy of the approach is tested through simulation and hardware implementation of two different prototypes. The Gen-I prototype was a single soft switched synchronous boost converter rated at 2.5kw. Both the motoring mode and regenerative modes of operation (Boost and Buck) were hardware tested for over 2kw and efficiency results of over 98.15% were achieved. The Gen-II prototype and the main focus of this work is an interleaved soft switched synchronous boost converter. This converter has been implemented in hardware as well and has been tested at 6.7kw and an efficiency of over 98% has been achieved in the boost mode of operation.
These targets for the converter are met through a number of different ways. The switches used are Silicon Carbide FETs. These are wide band gap (WBG) devices that can operate at high frequencies and temperatures. Since they allow for high frequency operation, a switching frequency of 250 khz is proposed and implemented. This helps with power density by reducing the size of passive components. High efficiencies are made possible by using a simple soft switching technique by augmenting the DC/DC converter with an auxiliary branch to enable zero voltage transition.
The efficacy of the approach is tested through simulation and hardware implementation of two different prototypes. The Gen-I prototype was a single soft switched synchronous boost converter rated at 2.5kw. Both the motoring mode and regenerative modes of operation (Boost and Buck) were hardware tested for over 2kw and efficiency results of over 98.15% were achieved. The Gen-II prototype and the main focus of this work is an interleaved soft switched synchronous boost converter. This converter has been implemented in hardware as well and has been tested at 6.7kw and an efficiency of over 98% has been achieved in the boost mode of operation.
ContributorsRaza, Bassam (Author) / Ayyanar, Raja (Thesis advisor) / Qin, Jiangchao (Committee member) / Lei, Qin (Committee member) / Arizona State University (Publisher)
Created2019
Description
Large-scale blackouts that have occurred across North America in the past few decades have paved the path for substantial amount of research in the field of security assessment of the grid. With the aid of advanced technology such as phasor measurement units (PMUs), considerable work has been done involving voltage stability analysis and power system dynamic behavior analysis to ensure security and reliability of the grid. Online dynamic security assessment (DSA) analysis has been developed and applied in several power system control centers. Existing applications of DSA are limited by the assumption of simplistic load profiles, which often considers a normative day to represent an entire year. To overcome these aforementioned challenges, this research developed a novel DSA scheme to provide security prediction in real-time for load profiles corresponding to different seasons. The major contributions of this research are to (1) develop a DSA scheme incorporated with PMU data, (2) consider a comprehensive seasonal load profile, (3) account for varying penetrations of renewable generation, and (4) compare the accuracy of different machine learning (ML) algorithms for DSA. The ML algorithms that will be the focus of this study include decision trees (DTs), support vector machines (SVMs), random forests (RFs), and multilayer neural networks (MLNNs).
This thesis describes the development of a novel DSA scheme using synchrophasor measurements that accounts for the load variability occurring across different seasons in a year. Different amounts of solar generation have also been incorporated in this study to account for increasing percentage of renewables in the modern grid. To account for the security of the operating conditions different ML algorithms have been trained and tested. A database of cases for different operating conditions has been developed offline that contains secure as well as insecure cases, and the ML models have been trained to classify the security or insecurity of a particular operating condition in real-time. Multiple scenarios are generated every 15 minutes for different seasons and stored in the database. The performance of this approach is tested on the IEEE-118 bus system.
This thesis describes the development of a novel DSA scheme using synchrophasor measurements that accounts for the load variability occurring across different seasons in a year. Different amounts of solar generation have also been incorporated in this study to account for increasing percentage of renewables in the modern grid. To account for the security of the operating conditions different ML algorithms have been trained and tested. A database of cases for different operating conditions has been developed offline that contains secure as well as insecure cases, and the ML models have been trained to classify the security or insecurity of a particular operating condition in real-time. Multiple scenarios are generated every 15 minutes for different seasons and stored in the database. The performance of this approach is tested on the IEEE-118 bus system.
ContributorsNATH, ANUBHAV (Author) / Pal, Anamitra (Thesis advisor) / Holbert, Keith (Committee member) / Wu, Meng (Committee member) / Arizona State University (Publisher)
Created2019
Description
The universe since its formation 13.7 billion years ago has undergone many changes. It began with expanding and cooling down to a temperature low enough for formation of atoms of neutral Hydrogen and Helium gas. Stronger gravitational pull in certain regions caused some regions to be denser and hotter than others. These regions kept getting denser and hotter until they had centers hot enough to burn the hydrogen and form the first stars, which ended the Dark Ages. These stars did not live long and underwent violent explosions. These explosions and the photons from the stars caused the hydrogen gas around them to ionize. This went on until all the hydrogen gas in the universe was ionized. This period is known as Epoch Of Reionization. Studying the Epoch Of Reionization will help understand the formation of these early stars, the timeline of the reionization and the formation of the stars and galaxies as we know them today. Studying the radiations from the 21cm line in neutral hydrogen, redshifted to below 200MHz can help determine details such as velocity, density and temperature of these early stars and the media around them.
The EDGES program is one of the many programs that aim to study the Epoch of Reionization. It is a ground-based project deployed in Murchison Radio-Astronomy Observatory in Western Australia. At ground level the Radio Frequency Interference from the ionosphere and various man-made transmitters in the same frequency range as the EDGES receiver make measurements, receiver design and extraction of useful data from received signals difficult. Putting the receiver in space can help majorly escape the RFI. The EDGES In Space is a proposed project that aims at designing a receiver similar to the EDGES receiver but for a cubesat.
This thesis aims at designing a prototype receiver that is similar in architecture to the EDGES low band receiver (50-100MHz) but is significantly smaller in size (small enough to fit on a PCB for a cubesat) while keeping in mind different considerations that affect circuit performance in space.
The EDGES program is one of the many programs that aim to study the Epoch of Reionization. It is a ground-based project deployed in Murchison Radio-Astronomy Observatory in Western Australia. At ground level the Radio Frequency Interference from the ionosphere and various man-made transmitters in the same frequency range as the EDGES receiver make measurements, receiver design and extraction of useful data from received signals difficult. Putting the receiver in space can help majorly escape the RFI. The EDGES In Space is a proposed project that aims at designing a receiver similar to the EDGES receiver but for a cubesat.
This thesis aims at designing a prototype receiver that is similar in architecture to the EDGES low band receiver (50-100MHz) but is significantly smaller in size (small enough to fit on a PCB for a cubesat) while keeping in mind different considerations that affect circuit performance in space.
ContributorsJambagi, Ashwini (Author) / Mauskopf, Philip (Thesis advisor) / Aberle, James T., 1961- (Thesis advisor) / Trichopoulos, Georgios (Committee member) / Arizona State University (Publisher)
Created2019
ContributorsASU Library. Music Library (Publisher)
Created2021-10-24
ContributorsASU Library. Music Library (Publisher)
Created2021-10-15
ContributorsPielemeier, Joshua (Performer) / Dawson, Hayden (Performer) / Turnage, Marissa (Performer) / ASU Library. Music Library (Publisher)
Created2021-11-06
ContributorsZhang, Wenxin (Performer) / Chen, Andrew (Performer) / ASU Library. Music Library (Publisher)
Created2022-04-10