Electrical & Computer Engineering Doctoral Work

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Power-Efficient Adaptive Memory Design and Optimization for Video and Deep Learning
(North Dakota State University, 2020) Das, Hritom
Memory devices such as Static Random-Access Memory (SRAM) and Dynamic Random-Access Memory (DRAM) are dominating members of today’s semiconductor industry. Most of the silicon area in a digital system is occupied by memory devices. The video decoder and deep learning are especially constrained by memory devices to process a large amount of data. For example, memory devices are consuming lots of power for video processing. Nowadays, all mobile electronics, such as mobile phones and laptops, are using video data a lot. Due to that, the battery life of mobile devices is highly dependent on power consumption of memory devices. To enhance the battery life of mobile devices, supply voltage can be scaled down. However, memory devices are error prone at low supply voltages. To obtain high quality video, a functionally stable memory design is needed, which means we must provide a higher VDD or use a larger memory cell. As a result, there will be a tradeoff between quality, and silicon area or power consumption. For mobile devices, memory needs to be designed to operate in the sub-threshold region to maximize battery life; however, reducing the supply voltage slows down memory devices, resulting in poor video quality. Hence, memory design is very complicated and time consuming. So, a smart way to design memory devices for a specific application is needed. Mathematical models can be developed to design memory devices based on specific requirements such as silicon area, while optimizing video quality for a target supply voltage. Similarly, optimized memory is needed to better support differentially private deep learning algorithms in local devices. This dissertation first develops a mathematical model for designing optimal memory devices for videos, then develops an optimized memory for differentially private deep learning systems in edge computing devices, and finally develops a run-time adaptable Error Correction Code (ECC) video storage scheme, with minimal area overhead and negligible video quality degradation, in order to significantly reduce power.
Variation, Energy Consumption, Latency, and Failure Aware Design for Memristive ANNs
(North Dakota State University, 2021) Liao, Zhiheng
As a novel non-volatile device, the memristive crossbar array has delivered many promises in giving low computation complexity, high energy efficiency, and high density for neuromorphic computing. However, the intrinsic variability of switching behavior, energy consumption, and stuck at fault are still major obstacles to their implementation. Here we report our investigations of a model that experimentally demonstrates the natural stochasticity of cycle-to-cycle variations. In addition, we propose three techniques to mitigate the adverse impact of cycle-to-cycle variations, optimize energy consumption, reduce system latency, and improve fault tolerance. The relationship of the level of conductance and cycle-to-cycle variation was studied, and experiment results show an optimal number of the levels to mitigate cycle-to-cycle variations in the system. Additionally, the system compresses the number of pulses when the conductance is updated by the pulse stimulus to reduce cycle-to-cycle variations, resulting in a great energy and latency reduction. What’s more, the fault tolerance of the memristor-based system has been improved by a novel weight mapping method. This work paves the way of adopting memristors for more efficient applications in the era of edge computing and the Internet of Things.
Creation and Implementation of the Innovation-Based Learning Framework: A Learning Analytics Approach
(North Dakota State University, 2022) Singelmann, Lauren
To meet the national and international call for creative and innovative engineers, many engineering departments and classrooms are striving to create more authentic learning spaces where students are actively engaging with design and innovation activities. For example, one model for teaching innovation is Innovation-Based Learning (IBL) where students learn fundamental engineering concepts and apply them to an innovation project with the goal of producing value outsidethe classroom. The model has been fairly successful, but questions still remain about how to best support students and instructors in open-ended innovation spaces. To answer these questions, learning analytics and educational data mining (LA/EDM) techniques were used to better understand student innovation in IBL settings. LA/EDM is a growing field with the goal of collecting and interpreting large amounts of educational data to support student learning. In this work, five LA/EDM algorithms and tools were developed: 1) the IBL framework which groups student actions into illustrative categories specific to innovation environments, 2) a classifier model that automatically groups student text into the categories of the framework, 3) classifier models that leverage the IBL framework to predict student success, 4) clustering models that group students with similar behavior, and 5) epistemic network analysis models that summarize temporal student behavior. For each of the five algorithms/tools, the design, development, assessment, and resulting implications are presented. Together, the results paint a picture of the affordances and challenges of teaching and learning innovation. The main insights gained are how language and temporal behavior provide meaningful information about students’ learning and innovation processes, the unique challenges that result from incorporating open-ended innovation into the classroom, and the impact of using LA/EDM tools to overcome these challenges.
Microwave Measurement of Grain and Biomass
(North Dakota State University, 2022) Striker, Ryan
Microwave measurement is a powerful method for mass prediction and grain detection. Existing systems are well adapted for small volume grain measurements, but cannot accommodate materials other than grain (e.g. biomass), which are larger in size or dimensional ratios. Therefore, an enlarged measuring system with unique design is needed. This new system’s large size improves measurement repeatability by capturing an average response for randomly aligned bulk samples. The system supports homogenous samples up to 0.5 m thick and 1 m square, and it has been validated from 1-50 GHz. By increasing the measurement system’s physical size relative to existing systems, it is now possible to measure the plants associated with these grains and seeds in a similar manner. Preliminary results for mixtures of grain and biomass are reported. Having been validated for grain measurements, the One Meter Fixture is next used to collect phase shift and attenuation data for a variety of grain and oil seed samples (soybean, canola and corn). Using multiple variable linear regression analysis, a comprehensive clean grain mass estimation model was developed based on the dielectric properties of the grain samples derived from the S-Parameters at 13 GHz. Dielectric (ε') constant / properties and phase shift were introduced into the regression models and generated a grain mass estimation result with R2 values of 0.976, 0.977 and 0.989 for soybean, canola and corn samples, respectively. The results indicate that RF sensing technology has the potential to provide more accurate non-contact sensing methods for estimating grain mass in multiple precision agricultural applications.
Impact of Inverter-Based Resources on Grid Dynamics
(North Dakota State University, 2022) Ekic, Almir
The increasing integration of renewable energy resources such as wind and solar into the electric power grid through power electronic inverters has changed grid dynamics and posed challenges to grid planning, operation, and protection. The growing penetration of renewable energy resources may drive the grid towards weak power grid conditions, under which grid stability issues may affect the operation of inverter-based renewable generators. To more accurately identify the weak grid conditions for guiding grid planning to prevent potential weak grid issues, a method for grid strength assessment is proposed by considering not only the impact the of interaction between interconnected renewable resources, but also the impact of the interactions between shunt capacitors interconnected through the power network. On this basis, we use a real-time digital simulator to explore inverter dynamics under different grid conditions including weak grid conditions. One of the major findings is that there are undesired transient events during the grid restoration process, and the undesired transient events become more significant when increasing the number of solar PV inverters or under weak grid operating conditions. This finding motivates us to study the impact of inverter dynamics on grid protection during the grid restoration period by using a real-time digital simulator. It is found that inverters can act as negative-sequence sources to inject negative-sequence currents into the grid during the grid restoration period and thus can adversely impact the performance of protection schemes based on negative sequence components and potentially cause relay maloperations during the grid restoration period, thus making system protection less secure and reliable.
Characterization of Inflationary and Deflationary Auscultatory Blood Pressure Measurements
(North Dakota State University, 2022) Alvarez, Enrique
This document is a paper-based dissertation. The dissertation is a collection of articles written by the author in the pursuit to develop a novel method to measure blood pressure (BP). The introduction chapter describes how the documents are interrelated. This work starts with the description of the development and design of a non-invasive medical device capable of measuring arterial BP with a combination of inflationary and deflationary procedures. In addition to the device, we conducted a human-based study to characterize the properties of the BP signal in the inflationary and deflationary curves. With the signals acquired, we focused on the uncertainty occurring when taking two consecutive BP measurements. The prototype was composed of 1) a modified off-the-shelf oscillometric BP system, 2) a contact microphone with an amplifier, and 3) a high-sensitivity pulse oximeter, and its control electronics. The device captured the cuff pressure signal, arterial skin-surface acoustics, and photoplethysmography (PPG). The captured signals were processed and analyzed. We focused our analysis on the characterization of the uncertainty of two consecutive BP measurements by studying the biosignals captured with the custom-made apparatus. Accurate non-invasive BP measurements are vital in preventing and treating many cardiovascular diseases. The “gold standard” for non-invasive procedures is the auscultatory method, which is based on detecting Korotkoff sounds while deflating an arm cuff. Using this method as a “gold standard” requires highly-trained technicians and has an intrinsic uncertainty in its BP predictions. In this document, we analyze and characterize the origins of BP uncertainty. By analyzing the captured bio signals we postulate an uncertainty model for two consecutive BP measurements. Our research group developed a computer-based simulation of auscultatory BP measurement uncertainty, and these modeled results were compared to a humansubject experiment with a group of 20 diverse-conditioned individuals. Uncertainties were categorized and quantified. The total computer-simulated uncertainty ranged between -8.4 mmHg to 8.4 mmHg in systolic BP and -8.4 mmHg to 8.3 mmHg in diastolic BP at a 95% confidence interval. The limits in the human-based study ranged from -8.3 mmHg to 8.3 mmHg in systolic BP and -16.7 mmHg to 4.2 mmHg in diastolic BP.
A Study of Inverter-Based Resources on Power Grid Operation Under Uncertain Operating Conditions
(North Dakota State University, 2022) Maharjan, Manisha
The electric power grid is undergoing a rapid change predominantly driven by high penetration levels of renewable energy resources (RERs) such as wind and solar. These resources are interfaced with the power grid through power electronic inverters that use control algorithms to define their performance characteristics. As a group, these types of resources are commonly referred to as inverter-based RERs (IB-RERs). While IB-RERs use power electronic controls to change active and reactive power injection, the fast inverter controls, separating the power source from the grid, have changed grid dynamics and posed new challenges to maintaining reliable and safe grid operation. Moreover, the variable nature of IB-RERs generation under uncertain weather conditions further challenge the grid operation under uncertain operating conditions resulting from an imbalance in electricity generation and demand. To effectively manage IB-RERs for providing reliable grid services, this dissertation studies the impact of IB-RERs on grid operation at the transmission- and distribution- levels while considering uncertain operating conditions. More specifically, the probabilistic collocation method is introduced to quantify the uncertainty of renewable generation and load demands on the distribution system operation. Also, the probabilistic collocation method is integrated with grid assessment to assess the grid stiffness under uncertain operating conditions. In addition, the impact of transmission-level disturbances on solar generator operation in distribution systems is investigated by a real-time electromagnetic simulator. The proposed method and analysis results are useful for guiding grid planning and operation to address the emerging issues of integrating the high penetration of IB-RERs into the power grid for reliable grid services.
A Study of Conformal Metasurfaces on Passive Beam Steering for Arrays
(North Dakota State University, 2022) Ge, Ruisi
Beam-steering has drawn significant interest due to the expansion of network capacity. However, a traditional beam steering system involves active phase shifters and controlling networks which can be complex. This work proposes a passive conformal metasurface design on beam steering. The phase shifting is achieved by changing the curvature of a conformal metasurface. In addition, three conformal prototypes were fabricated and tested using different techniques such as 3D printing. The simulations and test results indicate up to 20° of beam shifting. This study can be extended to higher frequency bands for lower power consumption beam steering systems.
Transformation Electromagnetics/Optics for Designing and Scanning Antenna Arrays
(North Dakota State University, 2021) Mitra, Dipankar
Recent developments in engineered electromagnetic materials, also known as metamaterials paved the way for new design approaches of unique and incomprehensible electromagnetic devices and structures using electromagnetic properties which are usually not available in nature. By taking advantage of Maxwell’s equation’s “form-invariance” under coordinate transformations, lately, a coordinate transformation-based approach was introduced to manipulate electromagnetic waves at will, which resulted in a non-homogeneous, anisotropic transformation media dictated by the coordinate transformation. This design approach is known as “transformation electromagnetics/optics (TE/TO)” and has steered many unconventional and seemingly-impossible unique electromagnetic devices such as, the electromagnetic invisibility cloak. The concepts of TE/TO can be extended to a region containing electromagnetic sources, which is known as source transformations. This research focused on the understanding of the theoretical and mathematical foundation of the “transformation electromagnetics/optics” and based on the understanding of the TE/TO concepts, a phased array antenna with new elements where antenna performance is a function of structural and mechanical constraints is proposed using source transformations, where each antenna element is “pinwheel” shaped antenna element transformed from a dipole element in free-space using appropriate coordinate transformations. The transformed materials are derived and through numerical simulations the radiation properties of the proposed array are demonstrated. It is anticipated that the proposed complex-geometry array will have great potential for future applications in structurally integrated and conformal arrays for wireless communications, radars, and sensing. Additionally, the TE/TO technique is employed to design a TO-based beam-steerer which enables beam-scanning with a single antenna element and an antenna array without using phase control circuits. The proposed beam-steerer is a TE/TO-based non-homogeneous, anisotropic material shell theoretically computed using coordinate transformations. Through full-wave simulations the beam-scanning performances of the TO-based beam-rotator was demonstrated and validated. Since the practical metamaterial implementation involves losses, numerical simulations are performed incorporating losses to the derived material parameters. While currently, numerical verifications are provided, in practice, these TO-approaches will require actively tunable material parameters. Significant advancements have been made by the material scientists to design tunable materials using different approaches, which could enable the implementation of the TO-based approach practically.
Turning Visual Noise Into Hardware Efficiency: Systems of Viewer and Content Aware Power-Quality Scalable Embedded Memories With ECC-Adaptation for Big Videos and Deep Learning
(North Dakota State University, 2021) Haidous, Ali Ahmad
Mobile devices, such as smart phones, are being increasingly utilized for watching videos. Video processing requires frequent memory access that consume a significant amount of power due to large data size and intensive computational requirements. This limits battery life and frustrates users. Memory designers are focused on hardware-level power-optimization techniques without consideration of how hardware performance influences viewers' actual experience. The human visual system is limited in its ability to detect subtle degradations in image quality. For example, under conditions of high ambient illumination – such as outdoors in direct sunlight – the veiling luminance (i.e., glare) on the screen of a mobile device can effectively mask imperfections in the image. Under these circumstances, a video can be rendered in lower than full quality without the viewer being able to detect any difference in quality. As a result, the isolation between hardware design and viewer experience significantly increases hardware implementation overhead and power consumption due to overly pessimistic design margins, while integrating the two would have the opposite effect. In this dissertation, viewer-awareness, content-awareness, and hardware adaptation are integrated to achieve power optimization without degrading video quality, as perceived by users. Specifically, this dissertation will (i) experimentally and mathematically connect viewer experience, ambient illuminance, and memory performance; (ii) develop energy-quality adaptive hardware that can adjust memory usage based on ambient luminance to reduce power usage without impacting viewer experience; (iii) design various mobile video systems to fully evaluate the effectiveness of the developed methodologies; and (iv) provide an overview of bleeding edge related area research then push the boundary further using the novel techniques discussed to achieve optimized quality, silicone area overhead, and power reduction in video memory.
Rare Molecule Biomarker Detection Using Dielectrophoresis Spectroscopy
(North Dakota State University, 2021) Gudagunti, Fleming Dackson
According to the American cancer society, 1.9 million new cancer cases and 608,570 cancer deaths are projected to occur in the United States. There is a fundamental technology gap that prevents the availability of tools for the diagnosis of cancer and genetic diseases as well as the genetic predisposition to developing certain diseases such as diabetes, and cardiovascular disease. The prognosis of several types of cancer can be done through blood tests to detect the concentration level of the respective biomarkers. However, detecting biomarkers is still difficult with existing methods such as ELISA, Surface Plasmon resonance, and PCR techniques. The existing techniques have drawbacks due to complicated and time-consuming protocols, thus requiring the presence of an expert to handle complex and expensive pieces of equipment. Therefore, there is a need to develop a cost-effective transduction mechanism for biomarker detectors that could be used for cancer screening at the point-of-care preferably using as a single finger-prick blood droplet from the patients that have the combination of high sensitivity, high specificity, and low complexity to detect cancer at an early stage. To address the limitations on the current techniques for biomarker detection, we developed a label-free automated real-time image processing technique based on dielectrophoresis (DEP) spectroscopy that is an effective transduction mechanism of a biosensor for the disease biomarker detection. A substantial change in the negative DEP force applied to functionalized polystyrene microspheres (PM) was observed to both the concentration level of the disease biomarker and the frequency of the electric field produced by interdigitated gold microelectrode. The velocity of repulsion of the PM attached to the disease biomarker from the electrode was determined using a side illumination and automated software using a real-time image processing technique that captures the Mie scattering from the PM. Since negative DEP spectroscopy is an effective transduction mechanism for the detection of the cutoff levels of disease biomarker, it has the potential to be used in the early-stage diagnosis and the prognosis of cancer.
Mitigating Nonlinear Effect and Preserving Privacy for Memristor Based On-Chip Neural Network
(North Dakota State University, 2021) Fu, Jingyan
Memristors offer advantages as a hardware solution for neuromorphic computing, however, their non-ideal property makes the weight update difficult and reduces the accuracy of a neural network. Also, a large amount of personal data has raised great concern about the privacy preservation of neural networks. Thus, the performance of memristor-based neural networks gets worse when considering non-ideal property and introducing a privacy preservation mechanism. This dissertation focuses on improving the performance of a memristor-based privacy-preserving neural network. A piecewise linear (PL) method is proposed to mitigate the nonlinear effect of memristors by calculating the weight update parameters along a piecewise line, which reduces errors in the weight update process. It mitigates the nonlinearity impact without reading the precise conductance of the memristor in each updating step, thereby avoiding complex peripheral circuits. What’s more., the PL method is proved to be an effective technique that can prevent accuracy loss and increase privacy preservation space for privacy-preserving ANN. Also, we propose a Noise Distribution Normalization (NDN) method to add Gaussian distributed noise through hardware implementation, thereby achieving differential privacy in edge AI. Instead of using traditional algorithmic noise-insertion methods, we take advantage of inherent cycle-to-cycle variations of memristors during the weight-update process as the noise source, which does not incur extra software or hardware overhead.
Synthesis of Specifications and Refinement Maps for Real-Time Object Code Verification
(North Dakota State University, 2020) Al-Qtiemat, Eman Mohammad
Formal verification methods have been shown to be very effective in finding corner-case bugs and ensuring the safety of embedded software systems. The use of formal verification requires a specification, which is typically a high-level mathematical model that defines the correct behavior of the system to be verified. However, embedded software requirements are typically described in natural language. Transforming these requirements into formal specifications is currently a big gap. While there is some work in this area, we proposed solutions to address this gap in the context of refinement-based verification, a class of formal methods that have shown to be effective for embedded object code verification. The proposed approach also addresses both functional and timing requirements and has been demonstrated in the context of safety requirements for software control of infusion pumps. The next step in the verification process is to develop the refinement map, which is a mapping function that can relate an implementation state (in this context, the state of the object code program to be verified) with the specification state. Actually, constructing refinement maps often requires deep understanding and intuitions about the specification and implementation, it is shown very difficult to construct refinement maps manually. To go over this obstacle, the construction of refinement maps should be automated. As a first step toward the automation process, we manually developed refinement maps for various safety properties concerning the software control operation of infusion pumps. In addition, we identified possible generic templates for the construction of refinement maps. Recently, synthesizing procedures of refinement maps for functional and timing specifications are proposed. The proposed work develops a process that significantly increases the automation in the generation of these refinement maps. The refinement maps can then be used for refinement-based verification. This automation procedure has been successfully applied on the transformed safety requirements in the first part of our work. This approach is based on the identified generic refinement map templates which can be increased in the future as the application required.
Bit Optimized Reconfigurable Network (BORN): A New Pathway Towards Implementing a Fully Integrated Band-Switchable CMOS Power Amplifier
(North Dakota State University, 2020) Hamidi Perchehkolaei, Seyyed Babak
The ultimate goal of the modern wireless communication industry is the full integration of digital, analog, and radio frequency (RF) functions. The most successful solution for such demands has been complementary metal oxide semiconductor (CMOS) technology, thanks to its cost-effective material and great versatility. Power amplifier (PA), the biggest bottleneck to integrate in a single-chip transceiver in wireless communications, significantly influences overall system performance. Recent advanced wireless communication systems demand a power amplifier that can simultaneously support different communication standards. A fully integrated single-chip tunable CMOS power amplifier is the best solution in terms of the cost and level of integration with other functional blocks of an RF transceiver. This work, for the first time, proposes a fully integrated band-switchable RF power amplifier by using a novel approach towards switching the matching networks. In this approach, which is called Bit Optimized Reconfigurable Network (BORN), two matching networks which can be controlled by digital bits will provide three operating frequency bands for the power amplifier. In order to implementing the proposed BORN PA, a robust high-power RF switch is presented by using resistive body floating technique and 6-terminal triple-well NMOS. The proposed BORN PA delivers measured saturated output power (Psat) of 21.25/22.25/ 23.0dBm at 960MHz/1317MHz/1750MHz, respectively. Moreover, the proposed BORN PA provides respective 3-dB bandwidth of 400MHz/425MHz/550MHz, output 1-dB compression point (P1dB) of 19.5dBm/20.0dBm/21.0dBm, and power-added efficiency (PAE) of 9/11/13% at three targeted frequency bands, respectively. The promising results show that the proposed BORN PA can be a practical solution for RF multiband applications in terms of the cost and level of integration with other functional blocks of an RF transceiver.
High Power Density and High Efficiency DC-DC Converters Based on Wide Bandgap Semiconductors
(North Dakota State University, 2019) Li, Yanchao
As the rapid development of semiconductor technologies, more and more power electronic devices are used in our daily life. The power converters are widely used in many emerging areas, such as renewable energy and clean electricity area, information technology (IT) area and transportation area. Due to the high power usage in all these areas, make the power converter highly efficient is becoming more important than ever. Also, high-density power converters are highly desired in more and more applications. Soft-switching technology is one of the key points that help us to achieve the goals. In this research work, a series of soft-switching power converters are presented and analyzed. First, a modular multilevel converter (MMC) with zero-current switching capability is proposed. By using different control method, the converter can achieve different voltage conversion ratios. Another attractive feature of the proposed MMC is that it can fully utilize the parasitic inductance existed in the converter system. Second, high power-density switched-capacitor converters start appearing in many emerging applications. On the one hand, the research proposed a multilevel switched-capacitor converter that is capable of zero-voltage switching (ZVS) and voltage regulation. On the other hand, a switched-tank converter with zero-current switching (ZCS) has been studied. Furthermore, adaptive control method has been proposed to solve the issues that are led by component tolerance during the mass production procedure. Besides, a comparison study of the two operation modes is performed. Also, a composite multilevel converter based on switched-capacitor concept has been developed for telecommunication application. Finally, a 100kW switched-tank converter has been developed to validate that the high power- density and high-efficiency can be achieved by using the switched-capacitor concept.
Analyses, Mitigation and Applications of Secure Hash Algorithms
(North Dakota State University, 2020) Al-Odat, Zeyad Abdel-Hameed
Cryptographic hash functions are one of the widely used cryptographic primitives with a purpose to ensure the integrity of the system or data. Hash functions are also utilized in conjunction with digital signatures to provide authentication and non-repudiation services. Secure Hash Algorithms are developed over time by the National Institute of Standards and Technology (NIST) for security, optimal performance, and robustness. The most known hash standards are SHA-1, SHA-2, and SHA-3. The secure hash algorithms are considered weak if security requirements have been broken. The main security attacks that threaten the secure hash standards are collision and length extension attacks. The collision attack works by finding two different messages that lead to the same hash. The length extension attack extends the message payload to produce an eligible hash digest. Both attacks already broke some hash standards that follow the Merkle-Damgrard construction. This dissertation proposes methodologies to improve and strengthen weak hash standards against collision and length extension attacks. We propose collision-detection approaches that help to detect the collision attack before it takes place. Besides, a proper replacement, which is supported by a proper construction, is proposed. The collision detection methodology helps to protect weak primitives from any possible collision attack using two approaches. The first approach employs a near-collision detection mechanism that was proposed by Marc Stevens. The second approach is our proposal. Moreover, this dissertation proposes a model that protects the secure hash functions from collision and length extension attacks. The model employs the sponge structure to construct a hash function. The resulting function is strong against collision and length extension attacks. Furthermore, to keep the general structure of the Merkle-Damgrard functions, we propose a model that replaces the SHA-1 and SHA-2 hash standards using the Merkle-Damgrard construction. This model employs the compression function of the SHA-1, the function manipulators of the SHA-2, and the $10*1$ padding method. In the case of big data over the cloud, this dissertation presents several schemes to ensure data security and authenticity. The schemes include secure storage, anonymous privacy-preserving, and auditing of the big data over the cloud.
Wide Band-Gap Semiconductor Based Power Converter Reliability and Topology Investigation
(North Dakota State University, 2020) Ni, Ze
Wide band-gap semiconductor materials such as silicon carbide (SiC) and gallium nitride (GaN) have been widely investigated these years for their preferred operation at higher switching frequency, higher blocking voltage, higher temperature, with a compacter volume, in comparison with the traditional silicon (Si) devices. SiC MOSFETs have been utilized in photovoltaic systems, wind turbine converters, electric vehicles, solid-state transformers, more electric ships, and airplanes. GaN based transistors have also been adopted in the DC-to-DC converters in data centers, personal computers, AC-to-DC power factor correction converters for the consumer electronic adaptors, and DC-to-AC photovoltaic micro-inverters. The first part of this dissertation is regarding the lifetime modeling and condition monitoring for the SiC MOSFETs. Since SiC-based devices have different failure modes and mechanisms compared with Si counterparts, a comprehensive review will be conducted to develop accurate lifetime prediction, condition monitoring, and lifetime extension strategies. First, a novel comprehensive online updated system-level lifetime modeling approach will be presented. Second, to monitor the SiC MOSFET ageing, the typical degradation indicators of SiC MOSFET gate oxide will be investigated. Third, to measure the junction temperature, the dynamic temperature-sensitive electrical parameters for the medium-voltage SiC devices will be studied. The other part is the topology investigation of these emerging wide band-gap devices. A generalized topology that would leverage the advantages of the wide band-gap devices will be introduced and analyzed in detail. Following it is a new evaluation index for comparing different topologies with the consideration of the semiconductor die information. The topology and its derivatives will be utilized in the subsequent chapters for three applications. First, a 100 kW switched tank converter (STC) will be designed using SiC MOSFETs for transportation power electronic systems. Second, an updated STC topology integrating with the partial-power voltage regulation will be introduced for electric vehicle applications. Third, two novel single-phase resonant multilevel modular boost inverters will be designed based on the voltage-regulated STC. These topologies will be validated through designed prototypes. As a result, the high power density and high efficiency will be realized by combining the well-suited topologies and the advantages of the WBG devices.
Formal Verification Methodologies for NULL Convention Logic Circuits
(North Dakota State University, 2020) Le, Son Ngoc
NULL Convention Logic (NCL) is a Quasi-Delay Insensitive (QDI) asynchronous design paradigm that aims to tackle some of the major problems synchronous designs are facing as the industry trend of increased clock rates and decreased feature size continues. The clock in synchronous designs is becoming increasingly difficult to manage and causing more power consumption than ever before. NCL circuits address some of these issues by requiring less power, producing less noise and electro-magnetic interference, and being more robust to Process, Voltage, and Temperature (PVT) variations. With the increase in popularity of asynchronous designs, a formal verification methodology is crucial for ensuring these circuits operate correctly. Four automated formal verification methodologies have been developed, three to ensure delay-insensitivity of an NCL circuit (i.e., prove Input-Completeness, Observability, and Completion-Completeness properties), and one to aid in proving functional equivalence between an NCL circuit and its synchronous counterpart. Note that an NCL circuit can be functionally correct and still not be input-complete, observable, or completion-complete, which could cause the circuit to operate correctly under normal conditions, but malfunction when circuit timing drastically changes (e.g., significantly reduced supply voltage, extreme temperatures). Since NCL circuits are implemented using dual-rail logic (i.e., 2 wires, rail0 and rail1, represent one bit of data), part of the functional equivalence verification involves ensuring that the NCL rail0 logic is the inverse of its rail1 logic. Equivalence verification optimizations and alternative invariant checking methods were investigated and proved to decrease verification times of identical circuits substantially. This work will be a major step toward NCL circuits being utilized more frequently in industry, since it provides an automated verification method to prove correctness of an NCL implementation and equivalence to its synchronous specification, which is the industry standard.
Utilization of Interdigitated Microelectrodes and Dielectrophoresis for Biosensing, Bio Molecule Manipulation and Biomanufacturing Therapeutic Cells
(North Dakota State University, 2020) Jayasooriya, Vidura Dhananjaya
Microelectrode arrays (MEA) and microfluidic systems are two of the most used technologies in Lab-on-a-chip (LOC) applications. These integrated and miniaturized systems are said to offer significant advantages in medical applications due to their high sensitivity, high throughput, lower material consumption, low cost, and enhanced Spatio-temporal control. Further, the physical laws at the micro-scale offer certain advantages in terms of the control of physical, biological and chemical properties in diagnostics or therapeutics at the cellular or molecular level. Moreover, these platforms are portable and can be easily designed for point-of-care diagnostics. Unfortunately, among various microelectrode and microfluidic technologies available today, only a few have been proven to be useful in clinical applications. One of the reasons behind this issue is the lack of efficient and sensitive methods to integrate the handling of biological materials in microfluidic devices. This has created a gap between real-world clinical applications and this emerging technology. To address this issue, in this work, externally applied electric fields have integrated with MEA and microfluidics systems. Moreover, this work has centered on dielectrophoresis, which is a result of the interaction between biological materials (e.g., DNA, RNA and cells) and external electric fields. Dielectrophoretic force (DEP force) was used to selectively manipulate biological materials within microfluidics devices. This capability opened up avenues for biosensing and biomanufacturing. This work was organized in the following manner: first, we investigated the production of DEP force, selectivity and limits. Second, the new knowledge learned from dielectrophoresis experiments was used to develop novel biomarker sensing technologies or sensors. Third, dielectrophoretic cell purification methods needed for the production of safe chimeric antigen receptor (CAR) T-cells for treating cancer, was investigated. Finally, a novel method for the manufacturing of viral vector-free CAR T-cells was developed. Results from these studies have shown that integration dielectrophoresis with MEA and microfluidics provides a new class of tools for unmet needs in clinical applications. Finally, fundamental studies on dielectrophoresis provide new insights into its origin and limits. Developed technologies could be used in clinical applications after validation.
Development of Performance Optimized Rotation Tolerant Viola-Jones Based Blackbird Detection, a Throughput Optimized Asynchronous Mac Implementation, and Automated Wheat Lodging Estimation
(North Dakota State University, 2020) Jalil, Nauman
The research described in this doctoral dissertation focuses on three main topics:1) performance optimization of the Viola-Jones Algorithm (VJA) for red-winged blackbird (Agelaius phoeniceus) detection, 2) further increasing performance of an already optimized asynchronous Multiply and Accumulate (MAC) unit, and 3) development of a framework to differentiate between lodging and non-lodging areas of a field from visible and multispectral aerial drone images. The first topic explores VJA rotational robustness, since VJA object detection is inherently not invariant to in-plane object rotation. An efficient method to detect rotated blackbirds is developed, which provides a balance between detection accuracy and computational cost. The second topic further optimizes a previously developed high-speed asynchronous 72+32×32 MAC, which was the fastest in the literature, resulting in a speedup of 1.36 while also decreasing area by 8%. The third topic develops a model to distinguish lodging from non-lodging plots, using a Support Vector Machine model trained with color, texture, Normalized Difference Vegetation Index (NDVI), and height features. The model prediction accuracy is around 90%, indicating good performance in distinguishing lodging from non-lodging plots.

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