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- Genre: Masters Thesis
- Status: Published
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
Description
This work analyzes and develops a point-of-load (PoL) synchronous buck converter using enhancement-mode Gallium Nitride (e-GaN), with emphasis on optimizing reverse conduction loss by using a well-known technique of placing an anti-parallel Schottky diode across the synchronous power device. This work develops an improved analytical switching model for the GaN-based converter with the Schottky diode using piecewise linear approximations.
To avoid a shoot-through between the power switches of the buck converter, a small dead-time is inserted between gate drive switching transitions. Despite optimum dead-time management for a power converter, optimum dead-times vary for different load conditions. These variations become considerably large for PoL applications, which demand high output current with low output voltages. At high switching frequencies, these variations translate into losses that contribute significantly to the total loss of the converter. To understand and quantify power loss in a hard-switching buck converter that uses a GaN power device in parallel with a Schottky diode, piecewise transitions are used to develop an analytical switching model that quantifies the contribution of reverse conduction loss of GaN during dead-time.
The effects of parasitic elements on the dynamics of the switching converter are investigated during one switching cycle of the converter. A designed prototype of a buck converter is correlated to the predicted model to determine the accuracy of the model. This comparison is presented using simulations and measurements at 400 kHz and 2 MHz converter switching speeds for load (1A) condition and fixed dead-time values. Furthermore, performance of the buck converter with and without the Schottky diode is also measured and compared to demonstrate and quantify the enhanced performance when using an anti-parallel diode. The developed power converter achieves peak efficiencies of 91.7% and 93.86% for 2 MHz and 400 KHz switching frequencies, respectively, and drives load currents up to 6A for a voltage conversion from 12V input to 3.3V output.
In addition, various industry Schottky diodes have been categorized based on their packaging and electrical characteristics and the developed analytical model provides analytical expressions relating the diode characteristics to power stage performance parameters. The performance of these diodes has been characterized for different buck converter voltage step-down ratios that are typically used in industry applications and different switching frequencies ranging from 400 KHz to 2 MHz.
To avoid a shoot-through between the power switches of the buck converter, a small dead-time is inserted between gate drive switching transitions. Despite optimum dead-time management for a power converter, optimum dead-times vary for different load conditions. These variations become considerably large for PoL applications, which demand high output current with low output voltages. At high switching frequencies, these variations translate into losses that contribute significantly to the total loss of the converter. To understand and quantify power loss in a hard-switching buck converter that uses a GaN power device in parallel with a Schottky diode, piecewise transitions are used to develop an analytical switching model that quantifies the contribution of reverse conduction loss of GaN during dead-time.
The effects of parasitic elements on the dynamics of the switching converter are investigated during one switching cycle of the converter. A designed prototype of a buck converter is correlated to the predicted model to determine the accuracy of the model. This comparison is presented using simulations and measurements at 400 kHz and 2 MHz converter switching speeds for load (1A) condition and fixed dead-time values. Furthermore, performance of the buck converter with and without the Schottky diode is also measured and compared to demonstrate and quantify the enhanced performance when using an anti-parallel diode. The developed power converter achieves peak efficiencies of 91.7% and 93.86% for 2 MHz and 400 KHz switching frequencies, respectively, and drives load currents up to 6A for a voltage conversion from 12V input to 3.3V output.
In addition, various industry Schottky diodes have been categorized based on their packaging and electrical characteristics and the developed analytical model provides analytical expressions relating the diode characteristics to power stage performance parameters. The performance of these diodes has been characterized for different buck converter voltage step-down ratios that are typically used in industry applications and different switching frequencies ranging from 400 KHz to 2 MHz.
ContributorsKoli, Gauri (Author) / Kitchen, Jennifer (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Ozev, Sule (Committee member) / Arizona State University (Publisher)
Created2020
Machine Learning-based Analysis of the Relationship Between the Human Gut Microbiome and Bone Health
Description
The Human Gut Microbiome (GM) modulates a variety of structural, metabolic, and protective functions to benefit the host. A few recent studies also support the role of the gut microbiome in the regulation of bone health. The relationship between GM and bone health was analyzed based on the data collected from a group of twenty-three adolescent boys and girls who participated in a controlled feeding study, during which two different doses (0 g/d fiber and 12 g/d fiber) of Soluble Corn Fiber (SCF) were added to their diet. This analysis was performed by predicting measures of Bone Mineral Density (BMD) and Bone Mineral Content (BMC) which are indicators of bone strength, using the GM sequence of proportions of 178 microbes collected from 23 subjects, by building a machine learning regression model. The model developed was evaluated by calculating performance metrics such as Root Mean Squared Error, Pearson’s correlation coefficient, and Spearman’s rank correlation coefficient, using cross-validation. A noticeable correlation was observed between the GM and bone health, and it was observed that the overall prediction correlation was higher with SCF intervention (r ~ 0.51). The genera of microbes that played an important role in this relationship were identified. Eubacterium (g), Bacteroides (g), Megamonas (g), Acetivibrio (g), Faecalibacterium (g), and Paraprevotella (g) were some of the microbes that showed an increase in proportion with SCF intervention.
ContributorsKetha Hazarath, Pravallika Reddy (Author) / Bliss, Daniel (Thesis advisor) / Whisner, Corrie (Committee member) / Dasarathy, Gautam (Committee member) / Arizona State University (Publisher)
Created2020
Description
Daily collaborative tasks like pushing a table or a couch require haptic communication between the people doing the task. To design collaborative motion planning algorithms for such applications, it is important to understand human behavior. Collaborative tasks involve continuous adaptations and intent recognition between the people involved in the task. This thesis explores the coordination between the human-partners through a virtual setup involving continuous visual feedback. The interaction and coordination are modeled as a two-step process: 1) Collecting data for a collaborative couch-pushing task, where both the people doing the task have complete information about the goal but are unaware of each other's cost functions or intentions and 2) processing the emergent behavior from complete information and fitting a model for this behavior to validate a mathematical model of agent-behavior in multi-agent collaborative tasks. The baseline model is updated using different approaches to resemble the trajectories generated by these models to human trajectories. All these models are compared to each other. The action profiles of both the agents and the position and velocity of the manipulated object during a goal-oriented task is recorded and used as expert-demonstrations to fit models resembling human behaviors. Analysis through hypothesis teasing is also performed to identify the difference in behaviors when there are complete information and information asymmetry among agents regarding the goal position.
ContributorsShintre, Pallavi Shrinivas (Author) / Zhang, Wenlong (Thesis advisor) / Si, Jennie (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2020
Description
The maximum theoretical efficiency of a terrestrial non-concentrated silicon solar cell is 29.4%, as obtained from detailed balance analysis. Over 90% of the current silicon photovoltaics market is based on solar cells with diffused junctions (Al-BSF, PERC, PERL, etc.), which are limited in performance by increased non-radiative recombination in the doped regions. This limitation can be overcome through the use of passivating contacts, which prevent recombination at the absorber interfaces while providing the selectivity to efficiently separate the charge carriers generated in the absorber. This thesis aims at developing an understanding of how the material properties of the contact affect device performance through simulations.The partial specific contact resistance framework developed by Onno et al. aims to link material behavior to device performance specifically at open circuit. In this thesis, the framework is expanded to other operating points of a device, leading to a model for calculating the partial contact resistances at any current flow. The error in calculating these resistances is irrelevant to device performance resulting in an error in calculating fill factor from resistances below 0.1% when the fill factors of the cell are above 70%, i.e., for cells with good passivation and selectivity.
Further, silicon heterojunction (SHJ) and tunnel-oxide based solar cells are simulated in 1D finite-difference modeling package AFORS-HET. The effects of material property changes on device performance are investigated using novel contact materials like Al0.8Ga0.2As (hole contact for SHJ) and ITO (electron contact for tunnel-oxide cells). While changing the bandgap and electron affinity of the contact affect the height of the Schottky barrier and hence contact resistivity, increasing the doping of the contact will increase its selectivity. In the case of ITO, the contact needs to have a work function below 4.2 eV to be electron selective, which suggests that other low work function TCOs (like AZO) will be more applicable as alternative dopant-free electron contacts. The AFORS-HET model also shows that buried doped regions arising from boron diffusion in the absorber can damage passivation and decrease the open circuit voltage of the device.
Further, silicon heterojunction (SHJ) and tunnel-oxide based solar cells are simulated in 1D finite-difference modeling package AFORS-HET. The effects of material property changes on device performance are investigated using novel contact materials like Al0.8Ga0.2As (hole contact for SHJ) and ITO (electron contact for tunnel-oxide cells). While changing the bandgap and electron affinity of the contact affect the height of the Schottky barrier and hence contact resistivity, increasing the doping of the contact will increase its selectivity. In the case of ITO, the contact needs to have a work function below 4.2 eV to be electron selective, which suggests that other low work function TCOs (like AZO) will be more applicable as alternative dopant-free electron contacts. The AFORS-HET model also shows that buried doped regions arising from boron diffusion in the absorber can damage passivation and decrease the open circuit voltage of the device.
ContributorsDasgupta, Sagnik (Author) / Holman, Zachary (Thesis advisor) / Onno, Arthur (Committee member) / Wang, Qing Hua (Committee member) / Arizona State University (Publisher)
Created2020
Description
Infants born before 37 weeks of pregnancy are considered to be preterm. Typically, preterm infants have to be strictly monitored since they are highly susceptible to health problems like hypoxemia (low blood oxygen level), apnea, respiratory issues, cardiac problems, neurological problems as well as an increased chance of long-term health issues such as cerebral palsy, asthma and sudden infant death syndrome. One of the leading health complications in preterm infants is bradycardia - which is defined as the slower than expected heart rate, generally beating lower than 60 beats per minute. Bradycardia is often accompanied by low oxygen levels and can cause additional long term health problems in the premature infant.The implementation of a non-parametric method to predict the onset of brady- cardia is presented. This method assumes no prior knowledge of the data and uses kernel density estimation to predict the future onset of bradycardia events. The data is preprocessed, and then analyzed to detect the peaks in the ECG signals, following which different kernels are implemented to estimate the shared underlying distribu- tion of the data. The performance of the algorithm is evaluated using various metrics and the computational challenges and methods to overcome them are also discussed.
It is observed that the performance of the algorithm with regards to the kernels used are consistent with the theoretical performance of the kernel as presented in a previous work. The theoretical approach has also been automated in this work and the various implementation challenges have been addressed.
It is observed that the performance of the algorithm with regards to the kernels used are consistent with the theoretical performance of the kernel as presented in a previous work. The theoretical approach has also been automated in this work and the various implementation challenges have been addressed.
ContributorsMitra, Sinjini (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Moraffah, Bahman (Thesis advisor) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2020
Description
The quest to find efficient algorithms to numerically solve differential equations isubiquitous in all branches of computational science. A natural approach to address
this problem is to try all possible algorithms to solve the differential equation and
choose the one that is satisfactory to one's needs. However, the vast variety of algorithms
in place makes this an extremely time consuming task. Additionally, even
after choosing the algorithm to be used, the style of programming is not guaranteed
to result in the most efficient algorithm. This thesis attempts to address the same
problem but pertinent to the field of computational nanoelectronics, by using PETSc
linear solver and SLEPc eigenvalue solver packages to efficiently solve Schrödinger
and Poisson equations self-consistently.
In this work, quasi 1D nanowire fabricated in the GaN material system is considered
as a prototypical example. Special attention is placed on the proper description
of the heterostructure device, the polarization charges and accurate treatment of the
free surfaces. Simulation results are presented for the conduction band profiles, the
electron density and the energy eigenvalues/eigenvectors of the occupied sub-bands
for this quasi 1D nanowire. The simulation results suggest that the solver is very
efficient and can be successfully used for the analysis of any device with two dimensional
confinement. The tool is ported on www.nanoHUB.org and as such is freely
available.
this problem is to try all possible algorithms to solve the differential equation and
choose the one that is satisfactory to one's needs. However, the vast variety of algorithms
in place makes this an extremely time consuming task. Additionally, even
after choosing the algorithm to be used, the style of programming is not guaranteed
to result in the most efficient algorithm. This thesis attempts to address the same
problem but pertinent to the field of computational nanoelectronics, by using PETSc
linear solver and SLEPc eigenvalue solver packages to efficiently solve Schrödinger
and Poisson equations self-consistently.
In this work, quasi 1D nanowire fabricated in the GaN material system is considered
as a prototypical example. Special attention is placed on the proper description
of the heterostructure device, the polarization charges and accurate treatment of the
free surfaces. Simulation results are presented for the conduction band profiles, the
electron density and the energy eigenvalues/eigenvectors of the occupied sub-bands
for this quasi 1D nanowire. The simulation results suggest that the solver is very
efficient and can be successfully used for the analysis of any device with two dimensional
confinement. The tool is ported on www.nanoHUB.org and as such is freely
available.
ContributorsBaikadi, Pranay Kumar Reddy (Author) / Vasileska, Dragica (Thesis advisor) / Goodnick, Stephen (Committee member) / Povolotskyi, Mykhailo (Committee member) / Arizona State University (Publisher)
Created2020
Description
Lattice-based Cryptography is an up and coming field of cryptography that utilizes the difficulty of lattice problems to design lattice-based cryptosystems that are resistant to quantum attacks and applicable to Fully Homomorphic Encryption schemes (FHE). In this thesis, the parallelization of the Residue Number System (RNS) and algorithmic efficiency of the Number Theoretic Transform (NTT) are combined to tackle the most significant bottleneck of polynomial ring multiplication with the hardware design of an optimized RNS-based NTT polynomial multiplier. The design utilizes Negative Wrapped Convolution, the NTT, RNS Montgomery reduction with Bajard and Shenoy extensions, and optimized modular 32-bit channel arithmetic for nine RNS channels to accomplish an RNS polynomial multiplication. In addition to a full software implementation of the whole system, a pipelined and optimized RNS-based NTT unit with 4 RNS butterflies is implemented on the Xilinx Artix-7 FPGA(xc7a200tlffg1156-2L) for size and delay estimates. The hardware implementation achieves an operating frequency of 47.043 MHz and utilizes 13239 LUT's, 4010 FF's, and 330 DSP blocks, allowing for multiple simultaneously operating NTT units depending on FGPA size constraints.
ContributorsBrist, Logan Alan (Author) / Chakrabarti, Chaitali (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Bliss, Daniel (Committee member) / Arizona State University (Publisher)
Created2020
Description
The primary goal of this thesis is to evaluate the influence of ethyl vinyl acetate (EVA) and polyolefin elastomer (POE) encapsulant types on the glass-glass (GG) photovoltaic (PV) module reliability. The influence of these two encapsulant types on the reliability of GG modules was compared with baseline glass-polymer backsheet (GB) modules for a benchmarking purpose. Three sets of modules, with four modules in each set, were constructed with two substrates types i.e. glass-glass (GG) and glass- polymer backsheet (GB); and 2 encapsulants types i.e. ethyl vinyl acetate (EVA) and polyolefin elastomer (POE). Each module set was subjected to the following accelerated tests as specified in the International Electrotechnical Commission (IEC) standard and Qualification Plus protocol of NREL: Ultraviolet (UV) 250 kWh/m2; Thermal Cycling (TC) 200 cycles; Damp Heat (DH) 1250 hours. To identify the failure modes and reliability issues of the stressed modules, several module-level non-destructive characterizations were carried out and they include colorimetry, UV-Vis-NIR spectral reflectance, ultraviolet fluorescence (UVF) imaging, electroluminescence (EL) imaging, and infrared (IR) imaging. The above-mentioned characterizations were performed on the front side of the modules both before the stress tests (i.e. pre-stress) and after the stress tests (i.e. post-stress). The UV-250 extended stress results indicated slight changes in the reflectance on the non-cell area of EVA modules probably due to minor adhesion loss at the cell and module edges. From the DH-1250 extended stress tests, significant changes, in both encapsulant types modules, were observed in reflectance and UVF images indicating early stages of delamination. In the case of the TC-200 stress test, practically no changes were observed in all sets of modules. From the above short-term stress tests, it appears although not conclusive at this stage of the analysis, delamination seems to be the only failure mode that could possibly be affecting the module performance, as observed from UV and DH extended stress tests. All these stress tests need to be continued to identify the wear-out failure modes and their impacts on the performance parameters of PV modules.
ContributorsBhaskaran, Rahul (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2020
Description
In the current photovoltaic (PV) industry, the O&M (operations and maintenance) personnel in the field primarily utilize three approaches to identify the underperforming or defective modules in a string: i) EL (electroluminescence) imaging of all the modules in the string; ii) IR (infrared) thermal imaging of all the modules in the string; and, iii) current-voltage (I-V) curve tracing of all the modules in the string. In the first and second approaches, the EL images are used to detect the modules with broken cells, and the IR images are used to detect the modules with hotspot cells, respectively. These two methods may identify the modules with defective cells only semi-qualitatively, but not accurately and quantitatively. The third method, I-V curve tracing, is a quantitative method to identify the underperforming modules in a string, but it is an extremely time consuming, labor-intensive, and highly ambient conditions dependent method. Since the I-V curves of individual modules in a string are obtained by disconnecting them individually at different irradiance levels, module operating temperatures, angle of incidences (AOI) and air-masses/spectra, all these measured curves are required to be translated to a single reporting condition (SRC) of a single irradiance, single temperature, single AOI and single spectrum. These translations are not only time consuming but are also prone to inaccuracy due to inherent issues in the translation models. Therefore, the current challenges in using the traditional I-V tracers are related to: i) obtaining I-V curves simultaneously of all the modules and substrings in a string at a single irradiance, operating temperature, irradiance spectrum and angle of incidence due to changing weather parameters and sun positions during the measurements, ii) safety of field personnel when disconnecting and reconnecting of cables in high voltage systems (especially field aged connectors), and iii) enormous time and hardship for the test personnel in harsh outdoor climatic conditions. In this thesis work, a non-contact I-V (NCIV) curve tracing tool has been integrated and implemented to address the above mentioned three challenges of the traditional I-V tracers.
This work compares I-V curves obtained using a traditional I-V curve tracer with the I-V curves obtained using a NCIV curve tracer for the string, substring and individual modules of crystalline silicon (c-Si) and cadmium telluride (CdTe) technologies. The NCIV curve tracer equipment used in this study was integrated using three commercially available components: non-contact voltmeters (NCV) with voltage probes to measure the voltages of substrings/modules in a string, a hall sensor to measure the string current and a DAS (data acquisition system) for simultaneous collection of the voltage data obtained from the NCVs and the current data obtained from the hall sensor. This study demonstrates the concept and accuracy of the NCIV curve tracer by comparing the I-V curves obtained using a traditional capacitor-based tracer and the NCIV curve tracer in a three-module string of c-Si modules and of CdTe modules under natural sunlight with uniform light conditions on all the modules in the string and with partially shading one or more of the modules in the string to simulate and quantitatively detect the underperforming module(s) in a string.
This work compares I-V curves obtained using a traditional I-V curve tracer with the I-V curves obtained using a NCIV curve tracer for the string, substring and individual modules of crystalline silicon (c-Si) and cadmium telluride (CdTe) technologies. The NCIV curve tracer equipment used in this study was integrated using three commercially available components: non-contact voltmeters (NCV) with voltage probes to measure the voltages of substrings/modules in a string, a hall sensor to measure the string current and a DAS (data acquisition system) for simultaneous collection of the voltage data obtained from the NCVs and the current data obtained from the hall sensor. This study demonstrates the concept and accuracy of the NCIV curve tracer by comparing the I-V curves obtained using a traditional capacitor-based tracer and the NCIV curve tracer in a three-module string of c-Si modules and of CdTe modules under natural sunlight with uniform light conditions on all the modules in the string and with partially shading one or more of the modules in the string to simulate and quantitatively detect the underperforming module(s) in a string.
ContributorsMurali, Sanjay (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Srinivasan, Devarajan (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2020