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Description
Wearable technology has brought in a rapid shift in the areas of healthcare and lifestyle management. The recent development and usage of wearable devices like smart watches has created significant impact in areas like fitness management, exercise tracking, sleep quality assessment and early diagnosis of diseases like asthma, sleep apnea etc. This thesis is dedicated to the development of wearable systems and algorithms to fulfill unmet needs in the area of cardiorespiratory monitoring.
First, a pneumotach based flow sensing technique has been developed and integrated into a face mask for respiratory profile tracking. Algorithms have been developed to convert the pressure profile into respiratory flow rate profile. Gyroscope-based correction is used to remove motion artifacts that arise from daily activities. By using Principal Component Analysis, the follow-up work established a unique respiratory signature for each subject based on the flow profile and lung parameters computed using the wearable mask system.
Next, wristwatch devices to track transcutaneous gases like oxygen (TcO2) and carbon dioxide (TcCO2), and oximetry (SpO2) have been developed. Two chemical sensing approaches have been explored. In the first approach, miniaturized low-cost commercial sensors have been integrated into the wristwatch for transcutaneous gas sensing. In the second approach, CMOS camera-based colorimetric sensors are integrated into the wristwatch, where a part of camera frame is used for photoplethysmography while the remaining part tracks the optical signal from colorimetric sensors.
Finally, the wireless connectivity using Bluetooth Low Energy (BLE) in wearable systems has been explored and a data transmission protocol between wearables and host for reliable transfer has been developed. To improve the transmission reliability, the host is designed to use queue-based re-request routine to notify the wearable device of the missing packets that should be re-transmitted. This approach avoids the issue of host dependent packet losses and ensures that all the necessary information is received.
The works in this thesis have provided technical solutions to address challenges in wearable technologies, ranging from chemical sensing, flow sensing, data analysis, to wireless data transmission. These works have demonstrated transformation of traditional bench-top medical equipment into non-invasive, unobtrusive, ergonomic & stand-alone healthcare devices.
First, a pneumotach based flow sensing technique has been developed and integrated into a face mask for respiratory profile tracking. Algorithms have been developed to convert the pressure profile into respiratory flow rate profile. Gyroscope-based correction is used to remove motion artifacts that arise from daily activities. By using Principal Component Analysis, the follow-up work established a unique respiratory signature for each subject based on the flow profile and lung parameters computed using the wearable mask system.
Next, wristwatch devices to track transcutaneous gases like oxygen (TcO2) and carbon dioxide (TcCO2), and oximetry (SpO2) have been developed. Two chemical sensing approaches have been explored. In the first approach, miniaturized low-cost commercial sensors have been integrated into the wristwatch for transcutaneous gas sensing. In the second approach, CMOS camera-based colorimetric sensors are integrated into the wristwatch, where a part of camera frame is used for photoplethysmography while the remaining part tracks the optical signal from colorimetric sensors.
Finally, the wireless connectivity using Bluetooth Low Energy (BLE) in wearable systems has been explored and a data transmission protocol between wearables and host for reliable transfer has been developed. To improve the transmission reliability, the host is designed to use queue-based re-request routine to notify the wearable device of the missing packets that should be re-transmitted. This approach avoids the issue of host dependent packet losses and ensures that all the necessary information is received.
The works in this thesis have provided technical solutions to address challenges in wearable technologies, ranging from chemical sensing, flow sensing, data analysis, to wireless data transmission. These works have demonstrated transformation of traditional bench-top medical equipment into non-invasive, unobtrusive, ergonomic & stand-alone healthcare devices.
ContributorsTipparaju, Vishal Varun (Author) / Xian, Xiaojun (Thesis advisor) / Forzani, Erica (Thesis advisor) / Blain Christen, Jennifer (Committee member) / Angadi, Siddhartha (Committee member) / Arizona State University (Publisher)
Created2020
Description
The rationale of this thesis is to provide a thorough understanding of spalling for semiconductor materials and develop a low temperature spalling technology that reduces the surface roughness of the spalled wafers for Photovoltaics applications.
ContributorsGuimera Coll, Pablo (Author) / Bertoni, Mariana I (Thesis advisor) / Meier, Rico (Committee member) / Holman, Zachary (Committee member) / Wang, Qing Hua (Committee member) / Arizona State University (Publisher)
Created2020
Description
An ongoing effort in the photovoltaic (PV) industry is to reduce the major manufacturing cost components of solar cells, the great majority of which are based on crystalline silicon (c-Si). This includes the substitution of screenprinted silver (Ag) cell contacts with alternative copper (Cu)-based contacts, usually applied with plating. Plated Cu contact schemes have been under study for many years with only minor traction in industrial production. One of the more commonly-cited barriers to the adoption of Cu-based contacts for photovoltaics is long-term reliability, as Cu is a significant contaminant in c-Si, forming precipitates that degrade performance via degradation of diode character and reduction of minority carrier lifetime. Cu contamination from contacts might cause degradation during field deployment if Cu is able to ingress into c-Si. Furthermore, Cu contamination is also known to cause a form of light-induced degradation (LID) which further degrades carrier lifetime when cells are exposed to light.
Prior literature on Cu-contact reliability tended to focus on accelerated testing at the cell and wafer level that may not be entirely replicative of real-world environmental stresses in PV modules. This thesis is aimed at advancing the understanding of Cu-contact reliability from the perspective of quasi-commercial modules under more realistic stresses. In this thesis, c-Si solar cells with Cu-plated contacts are fabricated, made into PV modules, and subjected to environmental stress in an attempt to induce hypothesized failure modes and understand any new vulnerabilities that Cu contacts might introduce. In particular, damp heat stress is applied to conventional, p-type c-Si modules and high efficiency, n-type c-Si heterojunction modules. I present evidence of Cu-induced diode degradation that also depends on PV module materials, as well as degradation unrelated to Cu, and in either case suggest engineering solutions to the observed degradation. In a forensic search for degradation mechanisms, I present novel evidence of Cu outdiffusion from contact layers and encapsulant-driven contact corrosion as potential key factors. Finally, outdoor exposures to light uncover peculiarities in Cu-plated samples, but do not point to especially serious vulnerabilities.
Prior literature on Cu-contact reliability tended to focus on accelerated testing at the cell and wafer level that may not be entirely replicative of real-world environmental stresses in PV modules. This thesis is aimed at advancing the understanding of Cu-contact reliability from the perspective of quasi-commercial modules under more realistic stresses. In this thesis, c-Si solar cells with Cu-plated contacts are fabricated, made into PV modules, and subjected to environmental stress in an attempt to induce hypothesized failure modes and understand any new vulnerabilities that Cu contacts might introduce. In particular, damp heat stress is applied to conventional, p-type c-Si modules and high efficiency, n-type c-Si heterojunction modules. I present evidence of Cu-induced diode degradation that also depends on PV module materials, as well as degradation unrelated to Cu, and in either case suggest engineering solutions to the observed degradation. In a forensic search for degradation mechanisms, I present novel evidence of Cu outdiffusion from contact layers and encapsulant-driven contact corrosion as potential key factors. Finally, outdoor exposures to light uncover peculiarities in Cu-plated samples, but do not point to especially serious vulnerabilities.
ContributorsKaras, Joseph (Author) / Bowden, Stuart (Thesis advisor) / Alford, Terry (Thesis advisor) / Tamizhmani, Govindasamy (Committee member) / Michaelson, Lynne (Committee member) / Arizona State University (Publisher)
Created2020
Description
There are increasing demands for gas sensors in air quality and human health monitoring applications. The qualifying sensor technology must be highly sensitive towards ppb level gases of interest, such as acetylene (C2H2), hydrogen sulfide (H2S), and volatile organic compounds. Among the commercially available sensor technologies, conductometric gas sensors with nanoparticles of oxide semiconductors as sensing materials hold significant advantages in cost, size, and cross-compatibility. However, semiconductor gas sensors must overcome some major challenges in thermal stability, sensitivity, humidity interference, and selectivity before potential widespread adoption in air quality and human health monitoring applications.
The focus of this dissertation is to tackle these issues by optimizing the composition and the morphology of the nanoparticles, and by innovating the structure of the sensing film assembled with the nanoparticles. From the nanoparticles perspective, the thermal stability of tin oxide nanoparticles with different Al dopant concentrations was studied, and the results indicate that within certain range of doping concentration, the dopants segregated at the grain surface can improve the thermal stability by stabilizing the grain boundaries.
From the sensing film perspective, a novel self-assembly approach was developed for copper oxide nanosheets and the sensor response towards H2S gas was revealed to decrease monotonically by more than 60% as the number of layers increase from 1 to 300 (thickness: 0.03-10 μm). Moreover, a sensing mechanism study on the humidity influence on H2S detection was performed to gain more understandings of the role of the hydroxyl group in the surface reaction, and humidity independent response was observed in the monolayer film at 325 ℃. With a more precise deposition tool (Langmuir-Blodgett trough), monolayer film of zinc oxide nanowires sensitized with gold catalyst was prepared, and highly sensitive and specific response to C2H2 in the ppb range was observed. Furthermore, the effect of surface topography of the monolayer film on stabilizing noble metal catalyst, and the sensitization mechanism of gold were investigated.
Lastly, a semiconductor sensor array was developed to analyze the composition of gases dissolved in transformer oil to demonstrate the industrial application of this sensor technology.
The focus of this dissertation is to tackle these issues by optimizing the composition and the morphology of the nanoparticles, and by innovating the structure of the sensing film assembled with the nanoparticles. From the nanoparticles perspective, the thermal stability of tin oxide nanoparticles with different Al dopant concentrations was studied, and the results indicate that within certain range of doping concentration, the dopants segregated at the grain surface can improve the thermal stability by stabilizing the grain boundaries.
From the sensing film perspective, a novel self-assembly approach was developed for copper oxide nanosheets and the sensor response towards H2S gas was revealed to decrease monotonically by more than 60% as the number of layers increase from 1 to 300 (thickness: 0.03-10 μm). Moreover, a sensing mechanism study on the humidity influence on H2S detection was performed to gain more understandings of the role of the hydroxyl group in the surface reaction, and humidity independent response was observed in the monolayer film at 325 ℃. With a more precise deposition tool (Langmuir-Blodgett trough), monolayer film of zinc oxide nanowires sensitized with gold catalyst was prepared, and highly sensitive and specific response to C2H2 in the ppb range was observed. Furthermore, the effect of surface topography of the monolayer film on stabilizing noble metal catalyst, and the sensitization mechanism of gold were investigated.
Lastly, a semiconductor sensor array was developed to analyze the composition of gases dissolved in transformer oil to demonstrate the industrial application of this sensor technology.
ContributorsMiao, Jiansong (Author) / Lin, Jerry Y.S. (Thesis advisor) / Forzani, Erica (Committee member) / Liu, Jingyue (Committee member) / Li, Jian (Committee member) / Arizona State University (Publisher)
Created2020
Description
The availability of data for monitoring and controlling the electrical grid has increased exponentially over the years in both resolution and quantity leaving a large data footprint. This dissertation is motivated by the need for equivalent representations of grid data in lower-dimensional feature spaces so that machine learning algorithms can be employed for a variety of purposes. To achieve that, without sacrificing the interpretation of the results, the dissertation leverages the physics behind power systems, well-known laws that underlie this man-made infrastructure, and the nature of the underlying stochastic phenomena that define the system operating conditions as the backbone for modeling data from the grid.
The first part of the dissertation introduces a new framework of graph signal processing (GSP) for the power grid, Grid-GSP, and applies it to voltage phasor measurements that characterize the overall system state of the power grid. Concepts from GSP are used in conjunction with known power system models in order to highlight the low-dimensional structure in data and present generative models for voltage phasors measurements. Applications such as identification of graphical communities, network inference, interpolation of missing data, detection of false data injection attacks and data compression are explored wherein Grid-GSP based generative models are used.
The second part of the dissertation develops a model for a joint statistical description of solar photo-voltaic (PV) power and the outdoor temperature which can lead to better management of power generation resources so that electricity demand such as air conditioning and supply from solar power are always matched in the face of stochasticity. The low-rank structure inherent in solar PV power data is used for forecasting and to detect partial-shading type of faults in solar panels.
The first part of the dissertation introduces a new framework of graph signal processing (GSP) for the power grid, Grid-GSP, and applies it to voltage phasor measurements that characterize the overall system state of the power grid. Concepts from GSP are used in conjunction with known power system models in order to highlight the low-dimensional structure in data and present generative models for voltage phasors measurements. Applications such as identification of graphical communities, network inference, interpolation of missing data, detection of false data injection attacks and data compression are explored wherein Grid-GSP based generative models are used.
The second part of the dissertation develops a model for a joint statistical description of solar photo-voltaic (PV) power and the outdoor temperature which can lead to better management of power generation resources so that electricity demand such as air conditioning and supply from solar power are always matched in the face of stochasticity. The low-rank structure inherent in solar PV power data is used for forecasting and to detect partial-shading type of faults in solar panels.
ContributorsRamakrishna, Raksha (Author) / Scaglione, Anna (Thesis advisor) / Cochran, Douglas (Committee member) / Spanias, Andreas (Committee member) / Vittal, Vijay (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2020
Description
Semantic image segmentation has been a key topic in applications involving image processing and computer vision. Owing to the success and continuous research in the field of deep learning, there have been plenty of deep learning-based segmentation architectures that have been designed for various tasks. In this thesis, deep-learning architectures for a specific application in material science; namely the segmentation process for the non-destructive study of the microstructure of Aluminum Alloy AA 7075 have been developed. This process requires the use of various imaging tools and methodologies to obtain the ground-truth information. The image dataset obtained using Transmission X-ray microscopy (TXM) consists of raw 2D image specimens captured from the projections at every beam scan. The segmented 2D ground-truth images are obtained by applying reconstruction and filtering algorithms before using a scientific visualization tool for segmentation. These images represent the corrosive behavior caused by the precipitates and inclusions particles on the Aluminum AA 7075 alloy. The study of the tools that work best for X-ray microscopy-based imaging is still in its early stages.
In this thesis, the underlying concepts behind Convolutional Neural Networks (CNNs) and state-of-the-art Semantic Segmentation architectures have been discussed in detail. The data generation and pre-processing process applied to the AA 7075 Data have also been described, along with the experimentation methodologies performed on the baseline and four other state-of-the-art Segmentation architectures that predict the segmented boundaries from the raw 2D images. A performance analysis based on various factors to decide the best techniques and tools to apply Semantic image segmentation for X-ray microscopy-based imaging was also conducted.
In this thesis, the underlying concepts behind Convolutional Neural Networks (CNNs) and state-of-the-art Semantic Segmentation architectures have been discussed in detail. The data generation and pre-processing process applied to the AA 7075 Data have also been described, along with the experimentation methodologies performed on the baseline and four other state-of-the-art Segmentation architectures that predict the segmented boundaries from the raw 2D images. A performance analysis based on various factors to decide the best techniques and tools to apply Semantic image segmentation for X-ray microscopy-based imaging was also conducted.
ContributorsBarboza, Daniel (Author) / Turaga, Pavan (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Jayasuriya, Suren (Committee member) / Arizona State University (Publisher)
Created2020
Description
Perovskite solar cells are the next generation organic-inorganic hybrid technology and have achieved remarkable efficiencies comparable to Si-based conventional solar cells. Since their inception in 2009 with an efficiency of 3.9%, they have improved tremendously over the past decade and recently demonstrated 25.2% efficiency for single-junction devices. There are a few hurdles, however, that prevent this technology from realizing their full potential, such as stability and toxicity of the perovskites. Apart from solution processing in the fabrication of perovskites, precursor composition plays a major role in determining the quality of the thin film and its general properties. This work studies novel approaches for improving the efficiency and stability of the perovskite solar cells with minimized toxicity. The effect of excess Pb on photo-degradation in MAPbI3 perovskites in an inverted device architecture was studied with a focus on improving stability and efficiency. Precursor concentration with 5% excess Pb was found to be optimal for better efficiency and stability against photo-degradation. Further improvements in efficiency were made possible through the addition of Zirconium Acetylacetonate as a secondary electron buffer layer. A concentration of 1.5mg/ml was found to be optimal for demonstrating better efficiency and stability. Partial substitution of Pb with non-toxic Sr was also studied for improving the stability of inverted devices. Using acetate-derived precursors, 10% Sr was introduced into perovskites for improvements to the stability of the device.
In another study, triple-cation perovskites with FAMACs cations were studied with doping different amounts of Phenyl Ethyl Ammonium (PEA) to induce a quasi 2D-3D structure for improved moisture stability. Doping the perovskite with 1.67% PEA was found to be best for improved morphology with fewer pinholes, which further resulted in better VOC and stability. A passivation effect for triple-cation perovskites was further proposed with the addition of a Guanidinium Iodide layer on the perovskite. Concentrations of 1mg/ml and 2mg/ml were demonstrated to be best for reducing defects and trap states and increasing the overall stability of the device.
In another study, triple-cation perovskites with FAMACs cations were studied with doping different amounts of Phenyl Ethyl Ammonium (PEA) to induce a quasi 2D-3D structure for improved moisture stability. Doping the perovskite with 1.67% PEA was found to be best for improved morphology with fewer pinholes, which further resulted in better VOC and stability. A passivation effect for triple-cation perovskites was further proposed with the addition of a Guanidinium Iodide layer on the perovskite. Concentrations of 1mg/ml and 2mg/ml were demonstrated to be best for reducing defects and trap states and increasing the overall stability of the device.
ContributorsYerramilli, Aditya (Author) / Alford, Terry (Thesis advisor) / Theodore, David (Committee member) / Chen, Yuanqing (Committee member) / Arizona State University (Publisher)
Created2020
Description
The molecular beam epitaxy growth of the III-V semiconductor alloy indium arsenide antimonide bismide (InAsSbBi) is investigated over a range of growth temperatures and V/III flux ratios. Bulk and quantum well structures grown on gallium antimonide (GaSb) substrates are examined. The relationships between Bi incorporation, surface morphology, growth temperature, and group-V flux are explored. A growth model is developed based on the kinetics of atomic desorption, incorporation, surface accumulation, and droplet formation. The model is applied to InAsSbBi, where the various process are fit to the Bi, Sb, and As mole fractions. The model predicts a Bi incorporation limit for lattice matched InAsSbBi grown on GaSb.The optical performance and bandgap energy of InAsSbBi is examined using photoluminescence spectroscopy. Emission is observed from low to room temperature with peaks ranging from 3.7 to 4.6 μm. The bandgap as function of temperature is determined from the first derivative maxima of the spectra fit to an Einstein single oscillator model. The photoluminescence spectra is observed to significantly broaden with Bi content as a result of lateral composition variations and the highly mismatched nature of Bi atoms, pairs, and clusters in the group-V sublattice.
A bowing model is developed for the bandgap and band offsets of the quinary alloy GaInAsSbBi and its quaternary constituents InAsSbBi and GaAsSbBi. The band anticrossing interaction due to the highly mismatched Bi atoms is incorporated into the relevant bowing terms. An algorithm is developed for the design of mid infrared GaInAsSbBi
quantum wells, with three degrees freedom to independently tune transition energy, in plane strain, and band edge offsets for desired electron and hole confinement.
The physical characteristics of the fundamental absorption edge of the relevant III-V binaries GaAs, GaSb, InAs, and InSb are examined using spectroscopic ellipsometry. A five parameter model is developed that describes the key physical characteristics of the absorption edge, including the bandgap energy, the Urbach tail, and the absorption coefficient at the bandgap.
The quantum efficiency and recombination lifetimes of bulk InAs0.911Sb0.089 grown by molecular beam epitaxy is investigated using excitation and temperature dependent steady state photoluminescence. The Shockley-Read-Hall, radiative, and Auger recombination lifetimes are determined.
A bowing model is developed for the bandgap and band offsets of the quinary alloy GaInAsSbBi and its quaternary constituents InAsSbBi and GaAsSbBi. The band anticrossing interaction due to the highly mismatched Bi atoms is incorporated into the relevant bowing terms. An algorithm is developed for the design of mid infrared GaInAsSbBi
quantum wells, with three degrees freedom to independently tune transition energy, in plane strain, and band edge offsets for desired electron and hole confinement.
The physical characteristics of the fundamental absorption edge of the relevant III-V binaries GaAs, GaSb, InAs, and InSb are examined using spectroscopic ellipsometry. A five parameter model is developed that describes the key physical characteristics of the absorption edge, including the bandgap energy, the Urbach tail, and the absorption coefficient at the bandgap.
The quantum efficiency and recombination lifetimes of bulk InAs0.911Sb0.089 grown by molecular beam epitaxy is investigated using excitation and temperature dependent steady state photoluminescence. The Shockley-Read-Hall, radiative, and Auger recombination lifetimes are determined.
ContributorsSchaefer, Stephen Thomas (Author) / Johnson, Shane R (Thesis advisor) / Zhang, Yong-Hang (Committee member) / Goryll, Michael (Committee member) / King, Richard (Committee member) / Arizona State University (Publisher)
Created2020
Description
Single-layer pentagonal materials have received limited attention compared with their counterparts with hexagonal structures. They are two-dimensional (2D) materials with pentagonal structures, that exhibit novel electronic, optical, or magnetic properties. There are 15 types of pentagonal tessellations which allow plenty of options for constructing 2D pentagonal lattices. Few of them have been explored theoretically or experimentally. Studying this new type of 2D materials with density functional theory (DFT) will inspire the discovery of new 2D materials and open up applications of these materials in electronic and magnetic devices.In this dissertation, DFT is applied to discover novel 2D materials with pentagonal structures. Firstly, I examine the possibility of forming a 2D nanosheet with the vertices of type 15 pentagons occupied by boron, silicon, phosphorous, sulfur, gallium, germanium or tin atoms. I obtain different rearranged structures such as a single-layer gallium sheet with triangular patterns. Then the exploration expands to other 14 types of pentagons, leading to the discoveries of carbon nanosheets with Cairo tessellation (type 2/4 pentagons) and other patterns. The resulting 2D structures exhibit diverse electrical properties. Then I reveal the hidden Cairo tessellations in the pyrite structures and discover a family of planar 2D materials (such as PtP2), with a chemical formula of AB2 and space group pa ̄3. The combination of DFT and geometries opens up a novel route for the discovery of new 2D materials. Following this path, a series of 2D pentagonal materials such as 2D CoS2 are revealed with promising electronic and magnetic applications. Specifically, the DFT calculations show that CoS2 is an antiferromagnetic semiconductor with a band gap of 2.24 eV, and a N ́eel temperature of about 20 K. In order to enhance the superexchange interactions between the ions in this binary compound, I explore the ternary 2D pentagonal material CoAsS, that lacks the inversion symmetry. I find out CoAsS exhibits a higher Curie temperature of 95 K and a sizable piezoelectricity (d11=-3.52 pm/V). In addition to CoAsS, 34 ternary 2D pentagonal materials are discovered, among which I focus on FeAsS, that is a semiconductor showing strong magnetocrystalline anisotropy and sizable Berry curvature. Its magnetocrystalline anisotropy energy is 440 μeV/Fe ion, higher than many other 2D magnets that have been found.
Overall, this work not only provides insights into the structure-property relationship of 2D pentagonal materials and opens up a new route of studying 2D materials by combining geometry and computational materials science, but also shows the potential applications of 2D pentagonal materials in electronic and magnetic devices.
Overall, this work not only provides insights into the structure-property relationship of 2D pentagonal materials and opens up a new route of studying 2D materials by combining geometry and computational materials science, but also shows the potential applications of 2D pentagonal materials in electronic and magnetic devices.
ContributorsLiu, Lei (Author) / Zhuang, Houlong (Thesis advisor) / Singh, Arunima (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2020
Description
A Single Event Transient (SET) is a transient voltage pulse induced by an ionizing radiation particle striking a combinational logic node in a circuit. The probability of a storage element capturing the transient pulse depends on the width of the pulse. Measuring the rate of occurrence and the distribution of SET pulse widths is essential to understand the likelihood of soft errors and to develop cost-effective mitigation schemes. Existing research measures the pulse width of SETs in bulk Complementary Metal-Oxide-Semiconductor (CMOS) and Silicon On Insulator (SOI) technologies, but not on Fin Field-Effect Transistors (FinFETs). This thesis focuses on developing a test structure on the FinFET process to generate, propagate, and separate SETs and build a time-to-digital converter to measure the pulse width of SET.
The proposed SET test structure statistically separates SETs generated at NMOS and PMOS based on the difference in restoring current. It consists of N-collection devices to collect events at NMOS and P-collection devices to collect events at PMOS. The events that occur in PMOS of the N-collection device and NMOS of the P-collection device are false events. The logic gates of the collection devices are skewed to perform pulse expansion so that a minimally sustained SET propagates without getting suppressed by the contamination delay. A symmetric tree structure with an S-R latch event detector localizes the location of the SET. The Cartesian coordinates-based pulse injection structure injects external pulses at specific nodes to perform instrumentation and calibrate the measurement. A thermometer-encoded chain (vernier chain) with mismatched delay paths measures the width of the SET.
For low Linear Energy Transfer (LET) tests, the false events are entirely masked and do not propagate since the amount of charge that has to be deposited for successful event propagation is significantly high. In the case of high LET tests, the actual events and false events propagate, but they can be separated based on the SET location and the width of the output event. The vernier chain has a high measurement resolution of ~3.5ps, which aids in separating the events.
The proposed SET test structure statistically separates SETs generated at NMOS and PMOS based on the difference in restoring current. It consists of N-collection devices to collect events at NMOS and P-collection devices to collect events at PMOS. The events that occur in PMOS of the N-collection device and NMOS of the P-collection device are false events. The logic gates of the collection devices are skewed to perform pulse expansion so that a minimally sustained SET propagates without getting suppressed by the contamination delay. A symmetric tree structure with an S-R latch event detector localizes the location of the SET. The Cartesian coordinates-based pulse injection structure injects external pulses at specific nodes to perform instrumentation and calibrate the measurement. A thermometer-encoded chain (vernier chain) with mismatched delay paths measures the width of the SET.
For low Linear Energy Transfer (LET) tests, the false events are entirely masked and do not propagate since the amount of charge that has to be deposited for successful event propagation is significantly high. In the case of high LET tests, the actual events and false events propagate, but they can be separated based on the SET location and the width of the output event. The vernier chain has a high measurement resolution of ~3.5ps, which aids in separating the events.
ContributorsShreedharan, Sanjay (Author) / Brunhaver, John (Thesis advisor) / Clark, Lawrence (Committee member) / Sanchez Esqueda, Ivan (Committee member) / Arizona State University (Publisher)
Created2020