Matching Items (103)
Filtering by
- All Subjects: Electrical Engineering
- Creators: Yu, Hongbin
- Creators: Ogras, Umit Y.
- Status: Published
Description
Since the invention of the automobile, engineers have been designing and making newer and newer improvements to them in order to provide customers with safer, faster, more reliable, and more comfortable vehicles. With each new generation, new technology can be seen being introduced into mainstream products, one of which that is currently being pushed is that of autonomy. Established brand manufacturers and small research teams have been dedicated for years to find a way to make the automobile autonomous with none of them being able to confidently answer that they have found a solution. Among the engineering community there are two schools of thought when solving this issue: camera and LiDAR; some believe that only cameras and computer vision are required while other believe that LiDAR is the solution. The most optimal case is to use both cameras and LiDAR’s together in order to increase reliability and ensure data confidence. Designers are reluctant to use LiDAR systems due to their massive weight, cost, and complexity; with too many moving components, these systems are very bulky and have multiple costly, moving parts that eventually need replacement due to their constant motion. The solution to this problem is to develop a solid-state LiDAR system which would solve all those issues previously stated and this research takes it one level further and looks into a potential prototype for a solid-state camera and Lidar package. Currently no manufacturer offers a system that contains a solid-state LiDAR system and a solid-state camera with computing capabilities, all manufacturers provided either just the camera, just the Lidar, or just the computation ability. This design will also use of the shelf COTS parts in order to increase reproducibility for open-source development and to reduce total manufacturing cost. While keeping costs low, this design is also able to keep its specs and performance on par with that of a well-used commercial product, the Velodyne VL50.
ContributorsEltohamy, Gamal (Author) / Yu, Hongbin (Thesis advisor) / Goryll, Michael (Committee member) / Allee, David (Committee member) / Arizona State University (Publisher)
Created2024
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 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
Description
Flexible hybrid electronics (FHE) is emerging as a promising solution to combine the benefits of printed electronics and silicon technology. FHE has many high-impact potential areas, such as wearable applications, health monitoring, and soft robotics, due to its physical advantages, which include light weight, low cost and the ability conform to different shapes. However, physical deformations that can occur in the field lead to significant testing and validation challenges. For example, designers have to ensure that FHE devices continue to meet specs even when the components experience stress due to bending. Hence, physical deformation, which is hard to emulate, has to be part of the test procedures developed for FHE devices. This paper is the first to analyze stress experience at different parts of FHE devices under different bending conditions. Then develop a novel methodology to maximize the test coverage with minimum number of text vectors with the help of a mixed integer linear programming formulation.
ContributorsGao, Hang (Author) / Ozev, Sule (Thesis advisor) / Ogras, Umit Y. (Committee member) / Christen, Jennifer Blain (Committee member) / Arizona State University (Publisher)
Created2018
Description
Medical ultrasound imaging is widely used today because of it being non-invasive and cost-effective. Flow estimation helps in accurate diagnosis of vascular diseases and adds an important dimension to medical ultrasound imaging. Traditionally flow estimation is done using Doppler-based methods which only estimate velocity in the beam direction. Thus when blood vessels are close to being orthogonal to the beam direction, there are large errors in the estimation results. In this dissertation, a low cost blood flow estimation method that does not have the angle dependency of Doppler-based methods, is presented.
First, a velocity estimator based on speckle tracking and synthetic lateral phase is proposed for clutter-free blood flow.
Speckle tracking is based on kernel matching and does not have any angle dependency. While velocity estimation in axial dimension is accurate, lateral velocity estimation is challenging due to reduced resolution and lack of phase information. This work presents a two tiered method which estimates the pixel level movement using sum-of-absolute difference, and then estimates the sub-pixel level using synthetic phase information in the lateral dimension. Such a method achieves highly accurate velocity estimation with reduced complexity compared to a cross correlation based method. The average bias of the proposed estimation method is less than 2% for plug flow and less than 7% for parabolic flow.
Blood is always accompanied by clutter which originates from vessel wall and surrounding tissues. As magnitude of the blood signal is usually 40-60 dB lower than magnitude of the clutter signal, clutter filtering is necessary before blood flow estimation. Clutter filters utilize the high magnitude and low frequency features of clutter signal to effectively remove them from the compound (blood + clutter) signal. Instead of low complexity FIR filter or high complexity SVD-based filters, here a power/subspace iteration based method is proposed for clutter filtering. Excellent clutter filtering performance is achieved for both slow and fast moving clutters with lower complexity compared to SVD-based filters. For instance, use of the proposed method results in the bias being less than 8% and standard deviation being less than 12% for fast moving clutter when the beam-to-flow-angle is $90^o$.
Third, a flow rate estimation method based on kernel power weighting is proposed. As the velocity estimator is a kernel-based method, the estimation accuracy degrades near the vessel boundary. In order to account for kernels that are not fully inside the vessel, fractional weights are given to these kernels based on their signal power. The proposed method achieves excellent flow rate estimation results with less than 8% bias for both slow and fast moving clutters.
The performance of the velocity estimator is also evaluated for challenging models. A 2D version of our two-tiered method is able to accurately estimate velocity vectors in a spinning disk as well as in a carotid bifurcation model, both of which are part of the synthetic aperture vector flow imaging (SA-VFI) challenge of 2018. In fact, the proposed method ranked 3rd in the challenge for testing dataset with carotid bifurcation. The flow estimation method is also evaluated for blood flow in vessels with stenosis. Simulation results show that the proposed method is able to estimate the flow rate with less than 9% bias.
First, a velocity estimator based on speckle tracking and synthetic lateral phase is proposed for clutter-free blood flow.
Speckle tracking is based on kernel matching and does not have any angle dependency. While velocity estimation in axial dimension is accurate, lateral velocity estimation is challenging due to reduced resolution and lack of phase information. This work presents a two tiered method which estimates the pixel level movement using sum-of-absolute difference, and then estimates the sub-pixel level using synthetic phase information in the lateral dimension. Such a method achieves highly accurate velocity estimation with reduced complexity compared to a cross correlation based method. The average bias of the proposed estimation method is less than 2% for plug flow and less than 7% for parabolic flow.
Blood is always accompanied by clutter which originates from vessel wall and surrounding tissues. As magnitude of the blood signal is usually 40-60 dB lower than magnitude of the clutter signal, clutter filtering is necessary before blood flow estimation. Clutter filters utilize the high magnitude and low frequency features of clutter signal to effectively remove them from the compound (blood + clutter) signal. Instead of low complexity FIR filter or high complexity SVD-based filters, here a power/subspace iteration based method is proposed for clutter filtering. Excellent clutter filtering performance is achieved for both slow and fast moving clutters with lower complexity compared to SVD-based filters. For instance, use of the proposed method results in the bias being less than 8% and standard deviation being less than 12% for fast moving clutter when the beam-to-flow-angle is $90^o$.
Third, a flow rate estimation method based on kernel power weighting is proposed. As the velocity estimator is a kernel-based method, the estimation accuracy degrades near the vessel boundary. In order to account for kernels that are not fully inside the vessel, fractional weights are given to these kernels based on their signal power. The proposed method achieves excellent flow rate estimation results with less than 8% bias for both slow and fast moving clutters.
The performance of the velocity estimator is also evaluated for challenging models. A 2D version of our two-tiered method is able to accurately estimate velocity vectors in a spinning disk as well as in a carotid bifurcation model, both of which are part of the synthetic aperture vector flow imaging (SA-VFI) challenge of 2018. In fact, the proposed method ranked 3rd in the challenge for testing dataset with carotid bifurcation. The flow estimation method is also evaluated for blood flow in vessels with stenosis. Simulation results show that the proposed method is able to estimate the flow rate with less than 9% bias.
ContributorsWei, Siyuan (Author) / Chakrabarti, Chaitali (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Ogras, Umit Y. (Committee member) / Wenisch, Thomas F. (Committee member) / Arizona State University (Publisher)
Created2018
Description
This dissertation proposes and presents two different passive sigma-delta
modulator zoom Analog to Digital Converter (ADC) architectures. The first ADC is fullydifferential, synthesizable zoom-ADC architecture with a passive loop filter for lowfrequency Built in Self-Test (BIST) applications. The detailed ADC architecture and a step
by step process designing the zoom-ADC along with a synthesis tool that can target various
design specifications are presented. The design flow does not rely on extensive knowledge
of an experienced ADC designer. Two example set of BIST ADCs have been synthesized
with different performance requirements in 65nm CMOS process. The first ADC achieves
90.4dB Signal to Noise Ratio (SNR) in 512µs measurement time and consumes 17µW
power. Another example achieves 78.2dB SNR in 31.25µs measurement time and
consumes 63µW power. The second ADC architecture is a multi-mode, dynamically
zooming passive sigma-delta modulator. The architecture is based on a 5b interpolating
flash ADC as the zooming unit, and a passive discrete time sigma delta modulator as the
fine conversion unit. The proposed ADC provides an Oversampling Ratio (OSR)-
independent, dynamic zooming technique, employing an interpolating zooming front-end.
The modulator covers between 0.1 MHz and 10 MHz signal bandwidth which makes it
suitable for cellular applications including 4G radio systems. By reconfiguring the OSR,
bias current, and component parameters, optimal power consumption can be achieved for
every mode. The ADC is implemented in 0.13 µm CMOS technology and it achieves an
SNDR of 82.2/77.1/74.2/68 dB for 0.1/1.92/5/10MHz bandwidth with 1.3/5.7/9.6/11.9mW
power consumption from a 1.2 V supply.
modulator zoom Analog to Digital Converter (ADC) architectures. The first ADC is fullydifferential, synthesizable zoom-ADC architecture with a passive loop filter for lowfrequency Built in Self-Test (BIST) applications. The detailed ADC architecture and a step
by step process designing the zoom-ADC along with a synthesis tool that can target various
design specifications are presented. The design flow does not rely on extensive knowledge
of an experienced ADC designer. Two example set of BIST ADCs have been synthesized
with different performance requirements in 65nm CMOS process. The first ADC achieves
90.4dB Signal to Noise Ratio (SNR) in 512µs measurement time and consumes 17µW
power. Another example achieves 78.2dB SNR in 31.25µs measurement time and
consumes 63µW power. The second ADC architecture is a multi-mode, dynamically
zooming passive sigma-delta modulator. The architecture is based on a 5b interpolating
flash ADC as the zooming unit, and a passive discrete time sigma delta modulator as the
fine conversion unit. The proposed ADC provides an Oversampling Ratio (OSR)-
independent, dynamic zooming technique, employing an interpolating zooming front-end.
The modulator covers between 0.1 MHz and 10 MHz signal bandwidth which makes it
suitable for cellular applications including 4G radio systems. By reconfiguring the OSR,
bias current, and component parameters, optimal power consumption can be achieved for
every mode. The ADC is implemented in 0.13 µm CMOS technology and it achieves an
SNDR of 82.2/77.1/74.2/68 dB for 0.1/1.92/5/10MHz bandwidth with 1.3/5.7/9.6/11.9mW
power consumption from a 1.2 V supply.
ContributorsEROL, OSMAN EMIR (Author) / Ozev, Sule (Thesis advisor) / Kitchen, Jennifer (Committee member) / Ogras, Umit Y. (Committee member) / Blain-Christen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2018
Description
As integrated technologies are scaling down, there is an increasing trend in the
process,voltage and temperature (PVT) variations of highly integrated RF systems.
Accounting for these variations during the design phase requires tremendous amount
of time for prediction of RF performance and optimizing it accordingly. Thus, there
is an increasing gap between the need to relax the RF performance requirements at
the design phase for rapid development and the need to provide high performance
and low cost RF circuits that function with PVT variations. No matter how care-
fully designed, RF integrated circuits (ICs) manufactured with advanced technology
nodes necessitate lengthy post-production calibration and test cycles with expensive
RF test instruments. Hence design-for-test (DFT) is proposed for low-cost and fast
measurement of performance parameters during both post-production and in-eld op-
eration. For example, built-in self-test (BIST) is a DFT solution for low-cost on-chip
measurement of RF performance parameters. In this dissertation, three aspects of
automated test and calibration, including DFT mathematical model, BIST hardware
and built-in calibration are covered for RF front-end blocks.
First, the theoretical foundation of a post-production test of RF integrated phased
array antennas is proposed by developing the mathematical model to measure gain
and phase mismatches between antenna elements without any electrical contact. The
proposed technique is fast, cost-efficient and uses near-field measurement of radiated
power from antennas hence, it requires single test setup, it has easy implementation
and it is short in time which makes it viable for industrialized high volume integrated
IC production test.
Second, a BIST model intended for the characterization of I/Q offset, gain and
phase mismatch of IQ transmitters without relying on external equipment is intro-
duced. The proposed BIST method is based on on-chip amplitude measurement as
in prior works however,here the variations in the BIST circuit do not affect the target
parameter estimation accuracy since measurements are designed to be relative. The
BIST circuit is implemented in 130nm technology and can be used for post-production
and in-field calibration.
Third, a programmable low noise amplifier (LNA) is proposed which is adaptable
to different application scenarios depending on the specification requirements. Its
performance is optimized with regards to required specifications e.g. distance, power
consumption, BER, data rate, etc.The statistical modeling is used to capture the
correlations among measured performance parameters and calibration modes for fast
adaptation. Machine learning technique is used to capture these non-linear correlations and build the probability distribution of a target parameter based on measurement results of the correlated parameters. The proposed concept is demonstrated by
embedding built-in tuning knobs in LNA design in 130nm technology. The tuning
knobs are carefully designed to provide independent combinations of important per-
formance parameters such as gain and linearity. Minimum number of switches are
used to provide the desired tuning range without a need for an external analog input.
process,voltage and temperature (PVT) variations of highly integrated RF systems.
Accounting for these variations during the design phase requires tremendous amount
of time for prediction of RF performance and optimizing it accordingly. Thus, there
is an increasing gap between the need to relax the RF performance requirements at
the design phase for rapid development and the need to provide high performance
and low cost RF circuits that function with PVT variations. No matter how care-
fully designed, RF integrated circuits (ICs) manufactured with advanced technology
nodes necessitate lengthy post-production calibration and test cycles with expensive
RF test instruments. Hence design-for-test (DFT) is proposed for low-cost and fast
measurement of performance parameters during both post-production and in-eld op-
eration. For example, built-in self-test (BIST) is a DFT solution for low-cost on-chip
measurement of RF performance parameters. In this dissertation, three aspects of
automated test and calibration, including DFT mathematical model, BIST hardware
and built-in calibration are covered for RF front-end blocks.
First, the theoretical foundation of a post-production test of RF integrated phased
array antennas is proposed by developing the mathematical model to measure gain
and phase mismatches between antenna elements without any electrical contact. The
proposed technique is fast, cost-efficient and uses near-field measurement of radiated
power from antennas hence, it requires single test setup, it has easy implementation
and it is short in time which makes it viable for industrialized high volume integrated
IC production test.
Second, a BIST model intended for the characterization of I/Q offset, gain and
phase mismatch of IQ transmitters without relying on external equipment is intro-
duced. The proposed BIST method is based on on-chip amplitude measurement as
in prior works however,here the variations in the BIST circuit do not affect the target
parameter estimation accuracy since measurements are designed to be relative. The
BIST circuit is implemented in 130nm technology and can be used for post-production
and in-field calibration.
Third, a programmable low noise amplifier (LNA) is proposed which is adaptable
to different application scenarios depending on the specification requirements. Its
performance is optimized with regards to required specifications e.g. distance, power
consumption, BER, data rate, etc.The statistical modeling is used to capture the
correlations among measured performance parameters and calibration modes for fast
adaptation. Machine learning technique is used to capture these non-linear correlations and build the probability distribution of a target parameter based on measurement results of the correlated parameters. The proposed concept is demonstrated by
embedding built-in tuning knobs in LNA design in 130nm technology. The tuning
knobs are carefully designed to provide independent combinations of important per-
formance parameters such as gain and linearity. Minimum number of switches are
used to provide the desired tuning range without a need for an external analog input.
ContributorsShafiee, Maryam (Author) / Ozev, Sule (Thesis advisor) / Diaz, Rodolfo (Committee member) / Ogras, Umit Y. (Committee member) / Bakkaloglu, Bertan (Committee member) / Arizona State University (Publisher)
Created2018
Description
Graphene has been extensively researched for both scientific and technological interests since its first isolation from graphite. The excellent transport properties and long spin diffusion length of graphene make it a promising material for electronic and spintronic device applications. This dissertation deals with the optimization of magnetic field sensing in graphene and the realization of nanoparticle induced ferromagnetism in graphene towards spintronic device applications.
Graphene has been used as a channel material for magnetic sensors demonstrating the potential for very high sensitivities, especially for Hall sensors, due to its extremely high mobility and low carrier concentration. However, the two-carrier nature of graphene near the charge neutrality point (CNP) causes a nonlinearity issue for graphene Hall sensors, which limits useful operating ranges and has not been fully studied. In this dissertation, a two-channel model was used to describe the transport of graphene near the CNP. The model was carefully validated by experiments and then was used to explore the optimization of graphene sensor performance by tuning the gate operating bias under realistic constraints on linearity and power dissipation.
The manipulation of spin in graphene that is desired for spintronic applications is limited by its weak spin-orbit coupling (SOC). Proximity induced ferromagnetism (PIFM) from an adjacent ferromagnetic insulator (FMI) provides a method for enhancing SOC in graphene without degrading its transport properties. However, suitable FMIs are uncommon and difficult to integrate with graphene. In this dissertation, PIFM in graphene from an adjacent Fe3O4 magnetic nanoparticle (MNP) array was demonstrated for the first time. Observation of the anomalous Hall effect (AHE) in the device structures provided the signature of PIFM. Comparison of the test samples with different control samples conclusively proved that exchange interaction at the MNP/graphene interface was responsible for the observed characteristics. The PIFM in graphene was shown to persist at room temperature and to be gate-tunable, which are desirable features for electrically controlled spintronic device applications.
The observation of PIFM in the MNP/graphene devices indicates that the spin transfer torque (STT) from spin-polarized current in the graphene can interact with the magnetization of the MNPs. If there is sufficient STT, spin torque oscillation (STO) could be realized in this structure. In this dissertation, three methods were employed to search for signatures of STO in the devices. STO was not observed in our devices, most likely due to the weak spin-polarization for current injected from conventional ferromagnetic contacts to graphene. Calculation indicates that graphene should provide sufficient spin-polarized current for exciting STO in optimized structures that miniaturize the device area and utilize optimized tunnel-barrier contacts for improved spin injection.
Graphene has been used as a channel material for magnetic sensors demonstrating the potential for very high sensitivities, especially for Hall sensors, due to its extremely high mobility and low carrier concentration. However, the two-carrier nature of graphene near the charge neutrality point (CNP) causes a nonlinearity issue for graphene Hall sensors, which limits useful operating ranges and has not been fully studied. In this dissertation, a two-channel model was used to describe the transport of graphene near the CNP. The model was carefully validated by experiments and then was used to explore the optimization of graphene sensor performance by tuning the gate operating bias under realistic constraints on linearity and power dissipation.
The manipulation of spin in graphene that is desired for spintronic applications is limited by its weak spin-orbit coupling (SOC). Proximity induced ferromagnetism (PIFM) from an adjacent ferromagnetic insulator (FMI) provides a method for enhancing SOC in graphene without degrading its transport properties. However, suitable FMIs are uncommon and difficult to integrate with graphene. In this dissertation, PIFM in graphene from an adjacent Fe3O4 magnetic nanoparticle (MNP) array was demonstrated for the first time. Observation of the anomalous Hall effect (AHE) in the device structures provided the signature of PIFM. Comparison of the test samples with different control samples conclusively proved that exchange interaction at the MNP/graphene interface was responsible for the observed characteristics. The PIFM in graphene was shown to persist at room temperature and to be gate-tunable, which are desirable features for electrically controlled spintronic device applications.
The observation of PIFM in the MNP/graphene devices indicates that the spin transfer torque (STT) from spin-polarized current in the graphene can interact with the magnetization of the MNPs. If there is sufficient STT, spin torque oscillation (STO) could be realized in this structure. In this dissertation, three methods were employed to search for signatures of STO in the devices. STO was not observed in our devices, most likely due to the weak spin-polarization for current injected from conventional ferromagnetic contacts to graphene. Calculation indicates that graphene should provide sufficient spin-polarized current for exciting STO in optimized structures that miniaturize the device area and utilize optimized tunnel-barrier contacts for improved spin injection.
ContributorsSong, Guibin (Author) / Kiehl, Richard A. (Committee member) / Yu, Hongbin (Committee member) / Chen, Tingyong (Committee member) / Rizzo, Nicholas D (Committee member) / Arizona State University (Publisher)
Created2019
Description
The detection and segmentation of objects appearing in a natural scene, often referred to as Object Detection, has gained a lot of interest in the computer vision field. Although most existing object detectors aim to detect all the objects in a given scene, it is important to evaluate whether these methods are capable of detecting the salient objects in the scene when constraining the number of proposals that can be generated due to constraints on timing or computations during execution. Salient objects are objects that tend to be more fixated by human subjects. The detection of salient objects is important in applications such as image collection browsing, image display on small devices, and perceptual compression.
This thesis proposes a novel evaluation framework that analyses the performance of popular existing object proposal generators in detecting the most salient objects. This work also shows that, by incorporating saliency constraints, the number of generated object proposals and thus the computational cost can be decreased significantly for a target true positive detection rate (TPR).
As part of the proposed framework, salient ground-truth masks are generated from the given original ground-truth masks for a given dataset. Given an object detection dataset, this work constructs salient object location ground-truth data, referred to here as salient ground-truth data for short, that only denotes the locations of salient objects. This is obtained by first computing a saliency map for the input image and then using it to assign a saliency score to each object in the image. Objects whose saliency scores are sufficiently high are referred to as salient objects. The detection rates are analyzed for existing object proposal generators with respect to the original ground-truth masks and the generated salient ground-truth masks.
As part of this work, a salient object detection database with salient ground-truth masks was constructed from the PASCAL VOC 2007 dataset. Not only does this dataset aid in analyzing the performance of existing object detectors for salient object detection, but it also helps in the development of new object detection methods and evaluating their performance in terms of successful detection of salient objects.
This thesis proposes a novel evaluation framework that analyses the performance of popular existing object proposal generators in detecting the most salient objects. This work also shows that, by incorporating saliency constraints, the number of generated object proposals and thus the computational cost can be decreased significantly for a target true positive detection rate (TPR).
As part of the proposed framework, salient ground-truth masks are generated from the given original ground-truth masks for a given dataset. Given an object detection dataset, this work constructs salient object location ground-truth data, referred to here as salient ground-truth data for short, that only denotes the locations of salient objects. This is obtained by first computing a saliency map for the input image and then using it to assign a saliency score to each object in the image. Objects whose saliency scores are sufficiently high are referred to as salient objects. The detection rates are analyzed for existing object proposal generators with respect to the original ground-truth masks and the generated salient ground-truth masks.
As part of this work, a salient object detection database with salient ground-truth masks was constructed from the PASCAL VOC 2007 dataset. Not only does this dataset aid in analyzing the performance of existing object detectors for salient object detection, but it also helps in the development of new object detection methods and evaluating their performance in terms of successful detection of salient objects.
ContributorsKotamraju, Sai Prajwal (Author) / Karam, Lina J (Thesis advisor) / Yu, Hongbin (Committee member) / Jayasuriya, Suren (Committee member) / Arizona State University (Publisher)
Created2019
Description
Wide bandgap (WBG) semiconductors GaN (3.4 eV), Ga2O3 (4.8 eV) and AlN (6.2 eV), have gained considerable interests for energy-efficient optoelectronic and electronic applications in solid-state lighting, photovoltaics, power conversion, and so on. They can offer unique device performance compared with traditional semiconductors such as Si. Efficient GaN based light-emitting diodes (LEDs) have increasingly displaced incandescent and fluorescent bulbs as the new major light sources for lighting and display. In addition, due to their large bandgap and high critical electrical field, WBG semiconductors are also ideal candidates for efficient power conversion.
In this dissertation, two types of devices are demonstrated: optoelectronic and electronic devices. Commercial polar c-plane LEDs suffer from reduced efficiency with increasing current densities, knowns as “efficiency droop”, while nonpolar/semipolar LEDs exhibit a very low efficiency droop. A modified ABC model with weak phase space filling effects is proposed to explain the low droop performance, providing insights for designing droop-free LEDs. The other emerging optoelectronics is nonpolar/semipolar III-nitride intersubband transition (ISBT) based photodetectors in terahertz and far infrared regime due to the large optical phonon energy and band offset, and the potential of room-temperature operation. ISBT properties are systematically studied for devices with different structures parameters.
In terms of electronic devices, vertical GaN p-n diodes and Schottky barrier diodes (SBDs) with high breakdown voltages are homoepitaxially grown on GaN bulk substrates with much reduced defect densities and improved device performance. The advantages of the vertical structure over the lateral structure are multifold: smaller chip area, larger current, less sensitivity to surface states, better scalability, and smaller current dispersion. Three methods are proposed to boost the device performances: thick buffer layer design, hydrogen-plasma based edge termination technique, and multiple drift layer design. In addition, newly emerged Ga2O3 and AlN power electronics may outperform GaN devices. Because of the highly anisotropic crystal structure of Ga2O3, anisotropic electrical properties have been observed in Ga2O3 electronics. The first 1-kV-class AlN SBDs are demonstrated on cost-effective sapphire substrates. Several future topics are also proposed including selective-area doping in GaN power devices, vertical AlN power devices, and (Al,Ga,In)2O3 materials and devices.
In this dissertation, two types of devices are demonstrated: optoelectronic and electronic devices. Commercial polar c-plane LEDs suffer from reduced efficiency with increasing current densities, knowns as “efficiency droop”, while nonpolar/semipolar LEDs exhibit a very low efficiency droop. A modified ABC model with weak phase space filling effects is proposed to explain the low droop performance, providing insights for designing droop-free LEDs. The other emerging optoelectronics is nonpolar/semipolar III-nitride intersubband transition (ISBT) based photodetectors in terahertz and far infrared regime due to the large optical phonon energy and band offset, and the potential of room-temperature operation. ISBT properties are systematically studied for devices with different structures parameters.
In terms of electronic devices, vertical GaN p-n diodes and Schottky barrier diodes (SBDs) with high breakdown voltages are homoepitaxially grown on GaN bulk substrates with much reduced defect densities and improved device performance. The advantages of the vertical structure over the lateral structure are multifold: smaller chip area, larger current, less sensitivity to surface states, better scalability, and smaller current dispersion. Three methods are proposed to boost the device performances: thick buffer layer design, hydrogen-plasma based edge termination technique, and multiple drift layer design. In addition, newly emerged Ga2O3 and AlN power electronics may outperform GaN devices. Because of the highly anisotropic crystal structure of Ga2O3, anisotropic electrical properties have been observed in Ga2O3 electronics. The first 1-kV-class AlN SBDs are demonstrated on cost-effective sapphire substrates. Several future topics are also proposed including selective-area doping in GaN power devices, vertical AlN power devices, and (Al,Ga,In)2O3 materials and devices.
ContributorsFu, Houqiang (Author) / Zhao, Yuji (Thesis advisor) / Vasileska, Dragica (Committee member) / Goodnick, Stephen (Committee member) / Yu, Hongbin (Committee member) / Wang, Liping (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