Our Research Projects

The Department of Electrical and Computer Engineering boasts an active and agile research community comprised of our nationally recognized staff, students, and collaborating colleagues. This cadre of scientists is bolstered by grants, both private and public, to further explore our field's unknown horizons.
Our department is filled with knowledgeable, astute individuals dedicated to uncovering new ideas and technology in the areas of Bioelectriconics, Communications, Computer Architecture, Nanoelectronics, and Power Systems. Our department encourages these efforts by providing a number of cutting-edge facilities and services to cultivate scientific progress.
Our research team is world recognized and funded by top names in both the public and private sectors. Government organization such as The National Science Foundation, The Army Research Office, and the U.S. Department of Energy, as well as corporations such as Cisco Systems, Qualcomm, Hewlett-Packard, and Red Hat have all allocated resources to further our research and development.
Our college has been awarded two Engineering Research Centers (ERCs) by the National Science Foundation.

These ERCs are part of a nation-wide group of university level interdisciplinary centers that work in partnership with local industry to pursue strategic solutions to complex engineering problems. ERCs have the potential to revolutionize entire products, systems, methodologies, and industries.

This support is a large reason why our college is ranked seventeenth in the nation in research expenditures and fourteenth in industry support, according to the American Society for Engineering Education (ASEE) in 2007.


Research in the Department of Electrical and Computer Engineering covers the gamut from basic to applied. Specific topics include not only those under our eight research areas, but themes such as novel ways to teach fundamental concepts, engineering as a life-long discipline, and the engineering education community.

The following list represents the projects currently active. Unfunded research is conducted continuously as the scientific curiosity of our faculty lead them to new areas of inquiry. Although we list only the principal investigators from each project, research is typically carried out through collaboration of the faculty, their students, and colleagues.

CAREER: Physical Side-Channels Beyond Cryptography: Transforming the Side-Channel Framework for Deep Learning

Aydin Aysu
10/01/2020 - 09/30/2025

Since its inception over two decades ago, physical side-channel analysis has been exclusively focusing on cryptographic implementations. Such research efforts deal with extracting secret cryptographic keys through their correlation to power/electromagnetic (EM) signals of a target embedded device and with methods to mitigate those vulnerabilities. Cryptography, however, is not the only application domain with confidentiality needs. Indeed, machine learning (ML) is a critical new target with a need for keeping the internal ML model secret. The move towards edge intelligence pushes ML to ubiquitous embedded devices making them the primary target for physical side-channel attacks. If leaked, not only the trademark model IP will be violated, but the ML system will be more vulnerable to adversarial attacks.

The research objective of this proposal is to extend physical side-channel analysis framework to deep neural network classifiers. We will first analyze how ML model parameters such as neural network weights can leak in hardware through power/EM measurements and demonstrate this vulnerability on an actual design. We will then formulate new, algorithmic (masking-based) defenses to construct provably-secure building blocks. Our ultimate goal is to automate secure-by-design neural network implementations by integrating composable defenses through high-level synthesis tools for hardware accelerators. The resulting solutions will be ported on FPGAs to benchmark overheads and be validated by extensive side-channel vulnerability tests.

The teaching goal of this proposal is to publish the first textbook and to introduce a new course on hardware security for ML. The PI has taught concepts related to this proposal in both undergraduate and graduate curricula but will consolidate those efforts into developing the new course. The course will target both undergraduate and graduate students with no prior background on ML or hardware security and will help them develop a thorough understanding of deep neural networks, implementation attacks, and real-world deployment challenges.

This project is sponsored by National Science Foundation (NSF).

Collaborative Research: NCS-FO: Intelligent Closed-Loop Neural Interface System for Studying Mechanisms of Somatosensory Feedback in Control of Functional and Stable Locomotion

Yaoyao Jia
09/01/2020 - 08/31/2023

Somatosensory feedback is critical for functional and dynamically stable locomotion. However, the mechanisms by which somatosensory feedback contributes to the coordination of muscle activity, limb dynamics, and body stability remain poorly understood. It is especially true for relatively large animals, like cats, whose limb inertia substantially affects limb dynamics, and the limb inertia must be compensated by precise muscle actions mediated by somatosensory feedback. Thus, it is important to perform experiments using the cat model system as cat locomotor mechanics and neural control are mechanically closer to humans than rodents. This project aims to investigate the mechanisms of somatosensory feedback from the spindle afferents of selected muscles on control of limb dynamics and dynamic stability in the cat model by developing an intelligent and closed-loop neural interface system. This project has three objectives. In objective 1, we will develop miniaturized, wirelessly-powered, and highly-integrated neural interface devices. These extremely small devices will be implanted in dorsal root ganglia (DRG) for high-channel-count neural recordings and optogenetic stimulations in a closed-loop manner. In objective 2, we will develop machine learning algorithms to map sensory neuron activities to muscle electrical activities (EMG) for achieving closed-loop control of the optogenetic neuromodulation. In objective 3, we will conduct in vivo studies on freely locomoting cats by recording neuron activities in DRG, EMG signals in selected muscles, and locomotor mechanics while selectively manipulating spindle afferent activities via optogenetic stimulation of the target neurons in DRG. The major innovation of this project is that we will for the first time perform selective and reversible activation and inhibition of spindle afferents in selected muscles of a relatively large animal (the cat) by applying optogenetic stimulation of the target neurons in an intelligent, closed-loop, and well-controlled manner. If successful, the results of this project and the developed methods will substantially enhance our understanding of the sensory control of locomotion in large animal models. Thus, this project well reflects the high-risk and high-payoff approach to advance the focus areas of the NCS program.

This project is sponsored by National Science Foundation (NSF).

Enhancing Undergraduate Learning About Biomechanics and Data Science Through Augmented Reality and Self-motion Data

Xu Xu, Xiaolei Fang, & Karen Boru Chen
09/01/2020 - 08/31/2023

Building upon contextual learning theories, we propose to establish a novel and mobile device-based learning platform to support and reinforce knowledge acquisition in biomechanics and data science

This project is sponsored by National Science Foundation (NSF).

Unifying biological and environmental data streams to monitor emerging lepidopteran resistance to genetically engineered crops

Anders Schmidt Huseth, George G. Kennedy, & Alper Yusuf Bozkurt
09/01/2020 - 08/31/2024

Accurate monitoring for changes in pest susceptibility to insecticidal toxins expressed in genetically engineered agronomic crops is currently an ineffective process limited by both scale and scope of deployment. Although long-term scientific and social change will be necessary to minimize pest resistance evolution, understanding near-term shifts in susceptibility through novel monitoring will also be essential to enable more effective resistance management strategies. To address this limitation on resistance monitoring, we propose to develop and deploy real-time pheromone-based sensor platforms to indicate patterns of lepidopteran pest activity in landscapes. We will use cotton bollworm (Helicoverpa zea Boddie) as a case study to develop and refine automated monitoring tools designed to detect shifts in pest susceptibility.

This project is sponsored by US Dept. of Agriculture (USDA) - National Institute of Food and Agriculture.

Collaborative Distributed Energy Management System (CoDEMS) for Optimal Energy Management in Microgrids. Phase 1.

Mo-Yuen Chow
08/10/2020 - 02/09/2021

To enhance the microgrid’s scalability, reliability, and resilience, this project aims to develop a collaborative and distributed energy management system (CoDEMS) that can determine globally optimal control commands without the need for a central coordinator. This phase of the project will develop a 2-node system that can provide an optimal charging and discharging schedule of the energy storage system using information from the grid support point and load forecast.

This project is sponsored by NC Electric Membership Corp..

Intergovernmental Personnel Act Agreement for Aryanya Chakrabortty

Aranya Chakrabortty
08/03/2020 - 08/02/2021

Dr. Chakrabortty will be serving as a program director in the ECCS division of NSF under an IPA agreement.

This project is sponsored by National Science Foundation (NSF).

Cover-2: Safety-as-a-Service

Yong Zhu, Alper Yusuf Bozkurt
08/01/2020 - 07/31/2021

Onda Vision Technologies, LLC (OVT) addresses the problem of early recognition of exertional heat illness in sports to enhance player safety and maximize performance. Exertional heat stroke, known as the silent killer, represents the most severe form of heat illness and stands as one of the top three leading causes of death among high school athletes with football having the highest rate. Since exertional heat stroke can cause permanent organ damage within a narrow time window (typically 30 – 60 minutes), early detection of exertional heat illness serves paramount to an athlete’s survival.

This project is sponsored by Onda Vision Technologies.

NRI: Fnd: A Novel Intervention Method to Promote Workers’ Safety Awareness and Mental Health During Human-Robot Collaboration

Xu Xu, Tianfu Wu, & Karen Boru Chen
08/01/2020 - 07/31/2023

The overall aim in this proposal is to develop and evaluate an intervention method to promote workers’ safety during human-robot collaboration

This project is sponsored by National Science Foundation (NSF).

SemiSynBio-II: Engineering Write, Access, Read, and Protect (WARP) Drives for DNA-based Data Storage Systems

Albert J. Keung, James Tuck, & Orlin D. Velev
08/01/2020 - 07/31/2023

This proposal will develop new systems for practical DNA-based information storage systems.

This project is sponsored by National Science Foundation (NSF).

Imaging Polarimetry for Measuring Bidirectional Reflectance and Metabolites in Maize

Michael Kudenov, Colleen J. Doherty
07/01/2020 - 06/30/2023

The purpose of this project is to develop a handheld Mueller matrix polarimeter that can be deployed to measure leaves in transmission. Leaves from different corn varieties will be quantified using both this handheld unit and our laboratory unit (an imaging Mueller Matrix polarimeter). These data will be compared to ground truth from e.g., enzymatic, colorimetric, 1D-NMR, and Mass-spectrometry based analyses, to correlate polarimetry measurements to metabolic concentration. Additionally, we will investigate polarization in reflection using a hyperspectral imaging polarimeter to quantify polarization’s ability to correct for bidirectional reflectance effects from canopy level measurements.

This project is sponsored by US Dept. of Agriculture (USDA) - National Institute of Food and Agriculture.

Implementation of Axion Electrodynamics in Topological Films and Devices

Ki Wook Kim
06/15/2020 - 06/14/2023

We propose to exploit the axion magnetoelectric response of topological materials – including topological insulators (TIs) and Weyl semimetals (WSMs) – to generate new routes to couple electric and magnetic degrees of freedom in materials and devices. The specific research objectives include: (1) theoretical analysis of novel topological materials and structures for strong axion coupling and (2) modeling of device applications for unique functionality. In the first task, the axionic properties of the TI based structures and magnetic WSMs will be systematically examined through a combination of model Hamiltonian treatments and first-principles calculations. The focus will be on multi-layered structures of TI and magnetic thin films that can realize axion insulators with a strong magnetoelectric response such as a large topological surface bandgap or charge polarization for room temperature operation. The investigation will also be extended to magnetic WSMs including those with antiferromagnetic ordering. The physical systems and properties identified in the analysis will then be exploited for potential device applications with unique functionality beyond the non-axionic counterparts. The concepts under consideration include transistor-like switches based on topological phase transition for steep turn-on/turn-off characteristics, tunable THz waveguide/modulator, and WSM based spintronics such as low-power nonvolatile domain-wall memory. The device exploration will start from the study of enabling physical mechanisms, followed by numerical studies for the feasibility demonstration and performance estimate. A multiscale approach will be applied as appropriate by using a suite of analytical and numerical treatments including micromagnetic simulations, Green’s functions, and finite difference time domain method.

This project is sponsored by Johns Hopkins University.

Enabling Magnetics for Solid State Transformers WFO

Subhashish Bhattacharya
06/08/2020 - 03/31/2021

Advances in grid-scale hardware and enabling technologies including materials, components, and component level modeling will play an important role in the modernization of the electricity transmission and distribution system. Large power transformers represent a major source of vulnerability and risk as catastrophic failures can represent major economic and social costs,driving the need for more standardized, modular, and readily deployable solid-state transformers.Iron core losses in distribution transformers represent a significant fraction of the overall losses in the transmission and distribution system. A rising prevalence of renewable and distributed energy
resources is increasing the deployment of grid-tied power electronics converters. Advanced sensing and control devices including current transformers and variable impedance power flow controllers will play a key role in enabling active power flow control. Solid state power substations are also a key part of any electrical generation, transmission, and distribution system and they
generally include transformers to (1) change voltage levels, (2) function as an interconnection between two transmission voltages, and (3) serve as control points for the flow of power to increase system reliability.

This project is sponsored by Oak Ridge Associated Universities.

Collaborative Research: RAPID: Understanding and Facilitating Remote Triage and Rehabilitation During Pandemics via Visual Based Patient Physiologic Sensing

Chau-Wai Wong
06/01/2020 - 05/31/2021

This RAPID project plans to investigate visual-based physiological sensing technologies to facilitate remote triage and rehabilitation during pandemics, by using low-cost consumer-grade cameras to track such physiological conditions as respiration rate, heart rate, and more from videos. The physiological data can be visualized and archived, and shared by users with medical practitioners to understand and support remote triage and rehabilitation.

The proposed research can enhance the interaction between medical providers and patients, and help address a projected surge in telehealth needs due to COVID-19. The PI team plans to conduct the first-of-a-kind data collection, by incorporating the novel contact-free video sensing into a biomedical cohort study that is being rolled out by a public-health collaboration team. This cross-disciplinary opportunity of multimodal data collection will offer insights on the relationship of multiple biosensing modalities, and the data collected would facilitate the research on early detection of COVID-19 and related diseases. The visual-based physiological sensing will also help enhance the remote interaction between rehabilitation therapists and patients during pandemics.

The intellectual merit of this effort lies in advancing promising engineering techniques of video-based contact-free physiological monitoring to support the rising needs of remote triage and rehabilitation during pandemics. The research findings and techniques developed address an important missing component in telehealth, which simultaneously achieves social-distancing, avoids hospital overcrowding, and prioritizes personal protective equipment in response to pandemics. By collaborating with another cohort study, an unprecedented multitude of data collected by the joint effort will provide key insights toward understanding and managing COVID-19 diseases and remote triage for future outbreaks. The timeliness of this opportunity cannot be met by any regular NSF programs other than the RAPID.

The project’s broader impact lies in two aspects. The multidisciplinary effort will provide important new knowledge and insights toward understanding and developing technology capabilities for remote triage and rehabilitation, which will contribute to the early detection, spread control, and effective management and prevention of future epidemics. The techniques developed through the project to support tele-rehabilitation will have a strong potential to improve the adverse conditions and quality of life of the affected citizens.

This project is sponsored by National Science Foundation (NSF).

Design and Implementation of a Software Stack for the Mapping of Finite State Transducers on the UDP

Michela Becchi
05/15/2020 - 09/30/2020

Design and implementation of a software stack for the mapping of finite state transducers on the UDP. This includes:
– Identifying a set of productions defining the grammar that will be initially supported (the grammar can be extended over time).
– Develop the code that converts the set of productions above into a finite state transducer
– Generate a compiler that, given a finite state transducer, generates UDP assembly code that implements its traversal.
– Generate synthetic data sets allowing experimenting with various degrees of parallelism
– If time allows, mapexisting data transformation schemes (such as huffman encoding or snappy compression) on a (extended) finite state transducer
– Compile a report

This project is sponsored by Argonne National Laboratory.

StarNAV: An Architecture for Autonomous Spacecraft Navigation by the Relativistic Perturbation of Starlight

Michael Kudenov
05/15/2020 - 01/14/2021

Exploration missions to the outer Solar System (e.g., Neptune, Kuiper belt objects) or to the interstellar medium present several challenges for conventional spacecraft designs. One of the greatest challenges is a means for navigation, as Earth-based tracking with the Deep Space Network (DSN) becomes less desirable due to high cost, decreased performance at long ranges, and long light-time delays. Indeed, light time delays at Neptune are over four hours (one way), making control of spacecraft during critical events nearly impossible—and this problem only becomes worse as we move to the Kuiper belt or to interstellar space. This proposal suggests a new (and completely different) way of autonomously navigating a spacecraft anywhere in the Solar System or beyond. We call this new technique StarNAV.

This project is sponsored by Rensselaer Polytechnic Institute.

Study on the High-Reliability and Low-Latency Communication Algorithm for Wireless Identification of Low-Altitude Small Drones

Ismail Guvenc, Mihail L. Sichitiu
05/01/2020 - 11/30/2020

Due to the tremendous growth of the drone industry, there is a growing concern for public safety and personal privacy. As drones become smarter and faster, remotely controlled drones can be utilized for illegal activities like nefarious surveillance of critical infrastructure or invasion of privacy. With the current anti-drone solution, it is difficult to deal with new challenges and threats. Note that anti-drone technologies can provide detection, location, tracking, identification, and mitigation against low-altitude small drones. Using the anti-drone technologies, law enforcement can easily detect abnormal behaviors and respond accordingly. First of all, we develop anti-drone technologies that can communicate a drone’s unique information (drone ID, etc.) to a ground node in order to deal with drone criminals and accidents. To this end, we will study high-reliability and low-latency communication algorithm for wireless identification of low-altitude small drones.

This project is sponsored by Electronics and Telecommunications Research Institute (ETRI).

Extendable Phased-Array Transceiver Platform

Brian Allan Floyd
04/01/2020 - 06/30/2020

In this program, we will investigate extendable phased-array architectures for microwave and millimeter-wave satellite communication networks. This will include invetigation of beamformer architectures, transceiver architectures, and overall system performance.

This project is sponsored by MaXentric Technologies, LLC.

Radio Disruption of Electronic Systems (RADES)

David Ricketts, Michael B. Steer
03/31/2020 - 07/06/2020

The design of electronics as well as the assessment of the performance of electronics relies on circuit- and system-level modeling but this can only be done with the assumption of a small range of performance parameters. Electronic systems are modeled only within the limits of intended signals. Modeling of realistic circuits at the transistor-level, with realistic signals, for realistic times, and for intentionally applied disruptive signals, cannot be undertaken. The typical assumption with radio communication electronics, for example, is to assume steady-state operation so that there is an inherent assumption in design that omits the behavior of electronic circuits and systems to unintended signals that are designed to induce disruption. NC State proposes to develop a modeling and exploration environment that will enable the modeling of the response of electronic systems to intentionally applied disruptive radio signals.

This project is sponsored by Vadum Inc..

Foliar Fungal Endophytes for Enhanced Sustainability and Resilience of Corn, Hemp, Soybean, Switchgrass, and Wheat

Christine Hawkes, Rosangela Sozzani, & Peter J. Balint-Kurti
02/17/2020 - 06/30/2023

More than a third of crop yields are currently lost due to abiotic and biotic stressors such as drought, pests, and disease. These stressors are expected to worsen in a warmer, drier future, resulting in crop yields further declining ~25%; however, breeding is only expected to rescue 7-15% of that loss [1]. The plant microbiome is a new avenue of plant management that may help fill this gap.

All plants have fungi living inside their leaves (“foliar fungal endophytes”). This is an ancient and intimate relationship in which the fungi affect plant physiology, biotic and abiotic stress tolerance, and productivity. For example, some foliar fungi prevent or delay onset of major yield-limiting diseases caused by pathogens such as Fusarium head blight [2]. Foliar endophytes also reduce plant water loss by up to half and delay wilting by several weeks [3, 4]. Endophyte effects on plants occur via diverse genes and metabolites, including genes involved in stress responses and plant defense [5]. Genes and metabolites also predict how interactions in fungal consortia affect host stress responses, which is important for developing field inoculations [6].

Because newly emergent leaves lack fungi, endophytes are also an attractive target for manipulation (particularly compared to soils, where competition with the existing microbial community inhibits microbial additives). We propose to address the role of endophytic “mycobiomes” in stress tolerance of five North Carolina food, fiber, and fuel crops (corn, hemp, soybean, switchgrass, wheat), and to develop tools that can push this field beyond its current limits. Our major objectives (Fig. 1) are to:
1. Identify key microbiome scales to optimally manage endophytes
2. Determine fungal mechanisms via greenhouse tests, modeling, and genetic engineering
3. Build tools for field detection of endophytes
4. Understand the regulatory environment and engage diverse stakeholders
Results of these objectives will allow us to make significant progress in both understanding the basic biology of plant-fungal interactions and managing those interactions in real-world settings. Our extension efforts will also bring these ideas to the broader community. Finally, we will also be well positioned to pursue several future research endeavors supported by federal granting agencies.

This project is sponsored by Game-Changing Research Incentive Program for Plant Sciences (GRIP4PSI).

Improving Crop Productivity and Value Through Heterogeneous Data Integration, Analytics, and Decision Support Platforms

Cranos Williams, Michael Kudenov, & Natalie Genevieve Nelson
02/17/2020 - 06/30/2023

Inconsistent quality and aesthetics in agricultural crops can result in increased consumer and producer food waste, reduced industry resiliency and decreased farmers’ and growers’ profit, poor consumer satisfaction, and inefficiencies across the supply chain. Although there are opportunities to characterize and quantify sources of phenotypic variability across the agricultural supply chain – from cultural practices of growers and producers to storage and handling by distributors – the data available to allow for assessment of horticultural quality drivers are disparate and disconnected. The absence of data integration platforms that link heterogeneous datasets across the supply chain precludes the development of strategies and solutions to constrain variability in produce quality. This project’s central hypothesis is that multi-dimensional produce data can be securely integrated and used to optimize management practices in the field while simultaneously adding value across the entire food supply chain. We propose to develop multi-modal sensing platform along with a trust-based, data management, integration, and analytics framework for systematic organization and dynamic abstraction of heterogeneous data across the supply chain of agricultural crops. The projects short term goals are to (1) engage growers to refine research and extension priorities; (2) develop a first-of-its-kind modular imaging system that responds to grower needs by analyzing existing and novel multi-dimensional data; (3) establish the cyberinfrastructure, including analytics and blockchain, to make meaningful inference of the acquired data as related to management practices while ensuring data security; (4) deploy the sensing system at NCSU’s Horticultural Crops Research Station in Clinton, NC and on a large-scale system at a major commercial farm and distribution facility, and (5) extend findings to producers and regulators through NC Cooperative Extension. The proposed sensing and cyberinfrastructure platforms will be crop-agnostic and our findings will be transferable to other horticultural crops produced in NC and beyond.

This project is sponsored by Game-Changing Research Incentive Program for Plant Sciences (GRIP4PSI).

Accurate Modeling of Indoor Environments Using a LiDAR for Efficient mmWave Network Planning and Understanding mmWave Propagation Channel Characteristics

Ismail Guvenc
02/05/2020 - 03/31/2020

There is ample literature on channel models and network planning for sub-6 GHz frequencies. However, since the channel propagation characteristics at millimeter-wave (mmWave) bands are significantly different from that of the sub-6 GHz bands, for reliable results, designated solutions are needed for mmWave systems. The major challenge with the mmWave frequencies is the high loss rates in terms of both free-space path loss and penetration losses. Therefore, while planning the mmWave network, it is utmost important to model the environment accurately, i.e., dimensions of the rooms, furniture, objects, material types, etc. In this project, we will use a LiDAR sensor for 3D mapping of indoor environments and transfer the created maps to Wireless InSite software to find the optimal base station (BS) locations that maximize the coverage rate. We will also generate binary occupancy maps from the LiDAR maps and use them along with the analytical channel models in machine learning algorithms to automate the mmWave BS placement. Indoor maps created with the LiDAR sensor will also provide the opportunity for a fair comparison between the channel measurements from the ray-tracing simulations and the measurements from the real-life experiments conducted with our NI-based channel sounder.

This project is sponsored by DOCOMO Innovations, Inc..

Developing a Path Forward for the Integration of the Coordinated Real-time Sub-Transmission Volt-Var Control Tool (CReST-VCT) into Energy Management Systems (EMS)

Ning Lu
01/06/2020 - 09/30/2020

DOE EERE SETO has been funding PNNL and North Carolina State University (NCSU) to develop a Coordinated Real-time Sub-Transmission Volt-Var Control Tool (CReST-VCT) to optimize the use of reactive power control devices to stabilize voltage fluctuations caused by intermittent solar photovoltaic (PV) outputs. CReST-VCT offers an innovative optimization approach for Volt/Var co-optimization of sub-transmission and distribution systems . This tool will remove a major roadblock to the increased use of distributed PV while maintain reliability of distribution and sub-transmission networks.
In this proposed project, PNNL and NCSU (tool developers) will work with ABB, a major commercial vendor of energy management systems (EMS) and distribution management systems (DMS), to develop a path forward for the integration of the CReST-VCT into the ABB EMS. We will identify issues related to communications requirements, interoperability, and compliance with revised IEEE 1547. Stakeholder outreach will be a key to commercialize the algorithms, models, and patents that have been developed in the SETO-funded project. We will survey utilities to understand their needs. We will talk to smart inverter vendors to understand what they can offer. Finally, we will develop a white paper on the recommended path forward for CReST-VCT commercialization.
CReST-VCT is built by PNNL based on algorithms that can coordinate the control logics of the existing grid reactive power compensation devices, from the sub-transmission system down to the distribution system, in addition to required VAr support from distributed PVs . At the distribution level, NCSU has developed a Voltage Sensitivity Matrix (VSM)-based optimal dispatch algorithm to coordinate customer-owned DERs with utility-owned devices for meeting the real and reactive power control objectives . An overview of CReST-VCT distribution Volt/Var optimization is shown in Figure 1. This tool will achieve one of EERE SETO’s systems integration (SI) goals by enabling increased use of distributed PV. The proposed tool achieves the OE Resilient distribution system (RDS) technology area goal of providing resilient grid services through management of all assets across the distribution power system.
The ultimate goal of this project is for PNNL and NSU to build a clear plan for integrating CReST-VCT into the ABB EMS/DMS systems and proposing this integration effort as a future Topic 2 TCF effort.

This project is sponsored by Pacific Northwest National Laboratory.

CPS: Small: Data-Driven Reinforcement Learning Control of Large CPS Networks using Multi-Stage Hierarchical Decompositions

Aranya Chakrabortty
01/01/2020 - 12/31/2022

In the current state-of-the-art machine learning based real-time control and decision-making in large-scale complex networks such as electric power systems is largely bottlenecked by the curse of dimensionality. Even the simplest linear quadratic regulator design demands cubic numerical complexity. The problem becomes even more complex when the network model is unknown, due to which an additional learning time needs to be accommodated. In this 3-year NSF CPS proposal, we take a new stance for solving this problem, and propose a hierarchical or nested machine learning-based scheme for real-time control of extreme-dimensional networks. Our approach will be to design appropriate projection matrices by which a network can be divided into disparate sets of non-overlapping groups depending on the low-rank properties of their controllability grammian, and multiple sets of composite controllers can be learned independently for each group using model-free reinforcement learning. Accordingly, the control goals of the network will also be decomposed into local (microscopic) and global (macroscopic) reward functions. Local controllers will be designed via privacy preserving group learning, and the global controllers via model reduction and averaging. Sparsity-promoting structures will be imposed on top of the local controllers to reduce their communication complexity. Deep learning algorithms based on historical events will be used to train recurrent neural networks so that they can rapidly predicting these sparse projections after any disturbance event in the network. Throughout this entire exercise, wide-area control of power systems using streaming Synchrophasor data from Phasor Measurements Units (PMUs) will be treated as a driving example. Results will be validated using standard IEEE models, a simplified model of the Japanese power grid with high-scale solar penetration, and an Opal-RT model of the Duke Energy power grid integrated with the ExoGENI cloud computing network at the FREEDM Systems Center.

This project is sponsored by National Science Foundation (NSF).

Data Analytics Using Advanced Meeting Data

Mesut E. Baran, Ning Lu
01/01/2020 - 12/31/2020

With new technologies such as AMI, utilities now have an abundance of data, however, they are doing very little with this data. Because of this situation, we will collaborate with our sponsor ElectriCities to investigate and develop applications for data analytics for utility operations and customers programs.

This project is sponsored by ElectriCities.

Extreme Fast Charging (“XFC”) for Plug-in Electric Vehicles

Subhashish Bhattacharya
01/01/2020 - 07/31/2022

Extreme fast charging (“XFC”) for plug-in electric vehicles: Medium Voltage XFC AC-DC Power Electronic converter System:
The schematic of three-phase medium voltage extreme fast charging AC-DC power electronic conversion system (XFC-ACDC) is shown in Fig. 1. The XFC-ACDC unit consists of three phase-modules whose input AC terminals are connected in Y-connection and their DC outputs are connected in parallel. The inputs of XFC-ACDC is connected to a 10 kV (Line-Line) three-phase MVAC grid and the output connected to a 1000 V DC bus across which various charging vehicles and equipment are integrated. Each phase-module of XFC-ACDC consists of a cascaded H-bridge converter and multiple dual active bridge converters (DABs). 1.7 kV SiC switches will be used for implementing the CHB and DAB converters. The voltages across the DC link capacitors of CHB will be maintained at 1.2 kV. The DABs will be regulated to maintain a voltage of 1000 V at their outputs.

This project is sponsored by Eaton Corporation.

FPGA Hardware Accelerator for Real Time Security, CAEML Core Project

Paul D. Franzon, Aydin Aysu
01/01/2020 - 12/31/2020

Build malware detector for detecting ransomware attacks in real time.

This project is sponsored by University of Illinois - Urbana-Champaign.

Potentiometric Detection of Neuropeptides for Non-Invasive Monitoring of Stress

Spyridon Pavlidis
01/01/2020 - 12/31/2020

The objective of this proposal is to demonstrate the detection of neuropeptide Y (NPY), a biomarker for stress found in human sweat, using gold-based potentiometric sensors that are compatible with ASSIST’s Health and Environmental Tracker (HET) 2.0 biochemical sensor architecture.

This project is sponsored by NCSU Advanced Self Powered Systems of Sensors and Technologies (ASSIST) Center.

Quantifying Cost-of-Service Impacts of Distributed Generation

Wenyuan Tang, Mesut E. Baran
01/01/2020 - 12/31/2020

This project will focus on investigating the impact of distributed generation (DG) on a utility distribution system from the cost-of-service perspective and developing a methodology to quantify those costs. The NCSU team will closely collaborate with the related groups in Duke Energy to determine which impacts can be reasonably quantified, present the developed methodology to the Public Staff and other stakeholders, and potentially file expert testimony in a general rate case. This project is primarily an engineering study, providing inputs to the rates department in Duke Energy, which will handle the rate design (i.e., how those costs should be allocated to DG).

This project is sponsored by Duke Energy Business Services LLC.

Si2 Power and Reliability Standards Development

William R. Davis
01/01/2020 - 05/15/2020

This effort will develop standards in collaboration with the Silicon Integration Initiative (Si2), including the Universal Power Model (UPM) and Compact Modeling Coalition (CMC) Open Model Interface (OMI) for Reliability Simulation. In addition, this effort will develop parallel computing methods for integrated circuit design databases.

This project is sponsored by Silicon Integration Initiative, Inc (Si2).

CNS Core: Small: Collaborative: Towards Surge-Resilient Hybrid RF/VLC Networks

Ismail Guvenc, Yavuz Yapici
11/01/2019 - 10/31/2022

The proposed research will study a hybrid RF/VLC network where the number of IoT users that require wireless communications is significantly
larger than the number of RF base stations (BSs). Our research is organized into three synergistic research thrusts. First, in Thrust-1, a novel, hybrid NOMA VLC/RF wireless access will be introduced, for which surge-resilient RAT/LED assignment and NOMA transmission techniques will be developed. The proposed approach can schedule UEs/MTDs based on their QoS needs under traffic surges and/or network failures. Subsequently, Thrust-2 will introduce novel, resilient cross-system learning for self-organizing resource management, and explore the network resilience against censored information, i.e., information that is not available to the network due to failures or environmental changes. The proposed cross-system learning framework allows for feedback between multiple learning algorithms operating across RATs to devise optimal resource allocation strategies that guarantee the required QoS levels across RATs, even when information is censored. Finally, Thrust-3 will introduce testbeds and SDR experimental platforms to evaluate the findings from the first two research thrusts on multihop RF/VLC communications and LED selection with NOMA.

This project is sponsored by National Science Foundation (NSF).

Developing a Combined System Model and Simulation Process for Integrated Planning and Operations across Transmission and Distribution Systems, CAPER Enhancement Project

David Lee Lubkeman, Ning Lu
11/01/2019 - 12/31/2020

In this project, the team will investigate the ability of performing steady state analysis of distributed energy resources (DER) at both the distribution and transmission levels with a combined model. Currently this analysis is often performed by Duke Energy using Siemens PTI’s PSS®E on the transmission level and using Eaton CYMDIST on the distribution level. The team will evaluate the ability to perform a unified DER analysis involving various types of T&D interconnections and potential interactions using a single simulation software tool(s) for analysis and planning of multiple network types. Given the increasing levels of DER devices seen at the distribution level, it is no longer feasible to perform only a distribution feeder-level analysis. Given the new ride-through and other requirements in the updated IEEE 1547 standard set, it will be necessary to evaluate the impact of transmission-level events to DER interconnections at the distribution-level to evaluate potential loss of DER generation. Also, the increased level of distribution DERs back-feeding into transmission is now impacting transmission-level operation and protection. Analyzing higher-penetration levels of DERs necessitates the need for an integrated analysis using a combined T & D model.

This project is sponsored by UNC - UNC Charlotte.

Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services

Ning Lu, Mesut E. Baran, & Srdjan Miodrag Lukic
11/01/2019 - 10/31/2022

In this project, we will develop a Photovoltaic Analysis and Response Support (PARS) platform for improving solar situation awareness and providing resiliency services. The team will focus on developing new operation modes for solar energy systems and a PV+DER situation awareness tool to enable accurate estimation and predication of PV and DER operation conditions in both normal operation conditions and in emergency operation when there is a wide spread outage caused by natural disasters or coordinated cyber attacks. Real-time dynamic studies will be conducted to compute system operation conditions for different operation options. This tool will be run on real-time simulation platform so that optimal restoration plans can be developed in real-time using operation modes enabled by Tasks 1 and parameters derived in Task 2. The team will model transmission, distribution, and all the way down to each DER and inverter units at utility scale PV farms on a multi-core OPAL-RT real-time simulation platform.

This project is sponsored by US Dept. of Energy (DOE) - Energy Efficiency & Renewable Energy (EERE).

Amorphous Metal Ribbon (AMR) and Metal Amorphous Nanocomposite (MANC) Materials Enabled High Power Density Vehicle Motor Applications

Subhashish Bhattacharya
10/01/2019 - 03/31/2022

Amorphous Metal Ribbon (AMR) and Metal Amorphous Nanocomposite (MANC) Materials Enabled High Power Density Vehicle Motor Applications.

A collaborative team from Carnegie Mellon Univ. (CMU), North Carolina State Univ. (NCSU) and Metglas, South Carolina proposes new high speed motors (HSMs) with high-power density for traction motors. These are enabled by hybrid designs exploiting permanent magnets without heavy rare earths and high induction/high resistivity soft magnetic materials allowing for high switching frequencies needed to increase power densities

This project is sponsored by Carnegie Mellon University.

Broadband Wireless Access and Applications Center (BWAC) Membership Pool Agreement

Ismail Guvenc
10/01/2019 - 09/30/2021

This project is sponsored by Broadband Wireless Access and Applications Center (BWAC) - Research Site at NCSU.

CNS Core: Medium: Thermodynamically-Driven Design of High Capacity, Practical DNA-Based Data Storage Systems

James Tuck, Albert J. Keung
10/01/2019 - 09/30/2023

Digital information is being generated in excess of 1 zettabyte (1021 bytes) per year worldwide. Existing information storage technologies are reaching major limitations in keeping pace. These limitations include unsustainable increases in the demand for: information capacity, physical storage space, raw materials, and energy to cool and maintain storage systems. DNA, a natural medium of information storage in biological systems, has garnered excitement and attention from both academic and industry groups as a potential next generation storage technology. DNA offers several advantages including a raw capacity of 1 zettabyte per 1 cubic centimeter. In comparison, state of the art electronic storage media would require 1000 cubic meters to store the same information. DNA also exhibits exceptional stability with a half-life of over a hundred years at ambient temperatures and requires minimal energy to maintain. Thus, DNA could be a transformative information storage medium. This project considers the design of a DNA-based data storage system from a thermodynamics perspective, allowing us to fine-tune interactions between DNA strands to achieve high capacity, random access, and search.

This project is sponsored by National Science Foundation (NSF).

Cybersecurity for Electric Power Systems

Mesut E. Baran, David M. Shafer, & Aranya Chakrabortty
10/01/2019 - 09/30/2022

Through multidisciplinary doctoral education in Cybersecurity for Electric Power Systems (CEPSE), North Carolina State University (NCSU) will increase its commitment to graduate training in two areas designated by the GAANN Program as critical to national need: Cybersecurity and Electrical Engineering. The goal of is to enlarge the pool of U.S. citizens and permanent residents who will pursue teaching and research careers in cybersecurity for electric power systems, thereby promoting workforce development and technological innovation impacting, national security, energy security, and environmental sustainability.

This project is sponsored by US Dept. of Education (DED).

Differential Power Analysis of Deep Neural Networks with Mitigation at the Architecture Level

Aydin Aysu, Paul D. Franzon
10/01/2019 - 09/30/2020

This proposal analyzes the vulnerability of deep neural network hardware implementations against power/electromagnetic side-channel attacks and their effective and automatic mitigation through architectural enhancements and compiler support. We will enhance RISC-V based microcontrollers through custom instruction extensions and use side-channel aware compilers to let programmers write side-channel secure software. The project will tape-out proof-of-concept chips with the proposed techniques.

This project is sponsored by Semiconductor Research Corporation.

High Efficiency Powertrain for Heavy Duty Trucks using SiC Inverter/Rectifier

Iqbal Husain, Srdjan Miodrag Lukic, & Wensong Yu
10/01/2019 - 12/31/2021

The proposal presents the plan for the development of a High Efficiency Powertrain (“HEP”) system will incorporate a combined high efficiency and compact SiC 250kW inverter/rectifier designed to support the high continuous loads and challenging shock/vibration environment of heavy-duty trucks with an electrified axle specifically designed for high performance and efficiency in battery-electric Class 8 trucks used in medium range (>250 mile) distribution. The SiC inverter/rectifier development will be led by Ricardo and supported by North Carolina State University (NCSU), Oak Ridge National Labs (ORNL) and Wolfspeed. Ricardo’s current 175kW inverter design (shown in Figure 1 above) shall act as the base for the new 250kW design. The goal of the new design is to maximize the combined inverter/motor efficiency as utilized in a Class 8 distribution truck running routes of >250 miles. Specifically, the goals are for the SiC inverter to reach efficiencies of 98.5% in a volume the same or smaller than the current 175kW design (more than 50kW/l). NCSU has also developed advanced SiC inverters and will support the new design in the areas of modeling optimization, planar designs including transformers, and minimizing commutation loop inductance and voltage stress of SiC devices. ORNL has performed extensive research and design work on SiC inverters and will focus on how to use the currently developed grid tied 1kV dc-bus link-based inverter power stage as the basis for an off-board DC-charger. Finally, Wolfspeed, one of the pre-eminent SiC MOSFET manufacturers in the world, will provide their leading-edge devices. We believe the combination of three strong SiC inverter designers coupled with the leading power module vendor will provide a very strong technical team for successful development of the advanced inverter and the converter for fast DC-charging.

This project is sponsored by Ricardo plc.

III: Small: Collaborative Research: Cost-Efficient Sampling and Estimation from Large-Scale Networks

Do Young Eun
10/01/2019 - 09/30/2022

Recent years have witnessed that online social networks (OSNs) change the way people interact with each other and trigger a tremendous amount of attention in various disciplines because of their extensive applications and massive useful data. They are simply too large to be downloaded or stored locally, and the sheer size forces us to resort to ‘sampling’ for estimation and inference of massive networks in a compact manner.
In particular, sampling via random-walk crawling has been commonly considered as the only viable solution, which is feasible via the public yet restrictive local-neighborhood-only interfaces provided by OSNs,
for estimating the properties of users (nodes), their relationships (edges), and more sophisticated relationship among multiple users (subgraph patterns). Whereas there have been many efforts in the literature to advance our understanding on sampling via random-walk crawling, there are still important challenges that have been generally overlooked and remained unsolved.

The long-term goal of the proposed research is to build a strong theoretical foundation for the optimal sampling strategies and the optimal control of multiple random walks for the estimation and inference of massive networks in the cost-constrained environments in reality, going beyond the current Markov Chain Monte Carlo (MCMC) driven statistical theories and practices for graph sampling in the literature.

This project is sponsored by National Science Foundation (NSF).

Indoor Ray Tracing and Base Station Placement Optimization for mmWave Systems, BWAC Core Project

Ismail Guvenc
10/01/2019 - 09/30/2020

Smart deployment of base stations (BSs) can help reduce the infrastructure costs while keeping the service quality at a desired minimum. The BS placement problem has been studied extensively for sub-6 GHz frequencies for both indoor and outdoor environments. However, the frequencies below 6 GHz are highly occupied, which makes frequencies at millimeter-wave (mmWave) bands attractive due to the vast amount of unused spectrum available for the fifth generation (5G) network. Besides, channel propagation characteristics of the mmWave band are significantly different from that of the sub-6 GHz band. mmWaves, due to using higher frequencies ranging from 30 to 300 GHz, are more vulnerable to blocking, and hence the presence of line-of-sight (LoS) links is more desired. Moreover, a typical mmWave link suffers an orders-of-magnitude larger path loss than a traditional sub-6 GHz link. Therefore, the mmWave network planning is more dependent on the layout of the environments. mmWave infrastructure also needs to be densely deployed to overcome the path loss and blockage problems, and to increase the LoS probability. This necessity may lead to many other problems, such as serious interference. The goal of this research is to understand the differences of network coverage in different bands for various indoor settings and to automate the mmWave BS placement with the aim of achieving high coverage with a minimum number of BSs.

This project is sponsored by Broadband Wireless Access and Applications Center (BWAC) - Research Site at NCSU.

Lean Entrepreneurship for U.S. Special Operations

John F. Muth, Lisa Iwen Chang
10/01/2019 - 02/14/2021

H4D is a class taught in over two dozen universities across the United States which focuses on teaching students Lean StartUp methods to apply to Department of Defense problems. NC State will develop and teach an H4D course in collaboration with the United States Special Operations Command (USSOCOM). All of the DoD problems introduced in this class will come from USSOCOM.

This project is sponsored by University of North Carolina System Office (formerly UNC - General Administration).

Membership in Broadband Wireless Access and Applications Center (BWAC) – NCSU Research Site

Ismail Guvenc
10/01/2019 - 09/30/2021

BWAC membership

This project is sponsored by DOCOMO Innovations, Inc..

SHF: Small: Collaborative Research: Accelerated Data Transformation: A Software-Hardware Stack for Transducers

Michela Becchi
10/01/2019 - 09/30/2022

Big Data’s growing importance is evident from broad application to business, public policy, medicine, and research. Many Big Data applications perform frequent data transformations on unstructured data. Data transformations can be mapped onto finite state transducers – a computational model with a solid theoretical foundation. The goal of this work is to design and develop a software stack for transducer processing that supports diverse platforms such as CPU’s, GPU’s, and efficient data-intensive accelerators (such as our Unstructured Data Processor). We summarize our research efforts as follows. First, we will create a high-level interface consisting of sets of production rules that can be mapped on transducers and can support a variety of data transformation operations. This interface will enable specification of flexible, extensible, and composable transducer programs. Second, we will build a sophisticated compiler that maps the high-level programming interface onto the finite state transducer computational model and includes optimization techniques that exploit the properties of this model. This compiler will produce an intermediate representation that can be mapped onto diverse hardware. Third, we will address software challenges involved with mapping the optimized finite state transducers onto a data-intensive accelerator, managing data-parallelism, limited memory, and generation of compact and efficient code that leverages the hardware features of the accelerator, particularly specialized operations. Finally, we will investigate the limitations of the finite state transducer model and extend it so to support more general data transformations performed in modern data analytics system. An example is block-based data compression and decompression, which we have demontrated can be efficiently supported by data-intensive accelerators, but cannot be expressed in the transducer model. We call this model unbounded transducers.

This project is sponsored by National Science Foundation (NSF).

SHF: Small: Collaborative Research: Efficient Memory Persistency for GPUs

Huiyang Zhou
10/01/2019 - 09/30/2022

This project investigates memory persistency models for GPUs.

This project is sponsored by National Science Foundation (NSF).

ROTC Research Experiences in Naval Electronic Warfare (RENEW)

Jacob James Adams, Michael B. Steer, & David Ricketts
09/30/2019 - 09/29/2020

A program providing research experiences and workshops in electronic warfare will be provided to ROTC cadets at NC State University and at neighboring colleges with the aim of presenting EW-focused workshops to all ROTC cadets at NC State University and close-by institutions. We will develop a research program for ROTC cadets in Electrical Engineering during the semester for NC State-based cadets and during the summer available to any US ROTC cadet. The emphasis will be on research experiences in wireless communication, radios, radars and sensors with the level of experience adapted to background. Students will learn how the range of architectures used in radios, radars and sensors; their vulnerabilities; how to identify vulnerabilities, and how they can be adapted to mitigate effects.

This project is sponsored by US Navy-Office Of Naval Research.

Collaborative Research: Improving the Performance and Design of Potentiometric Biosensors for the Detection of Extracellular Histones in Blood with Deep Learning

Spyridon Pavlidis, Edgar J Lobaton
09/15/2019 - 08/31/2022

The objective of the proposed research is to enable the rapid translation from aptamer selection to deployment on a potentiometric biosensor’s surface for highly selective detection. Optimization of the sensor surface will be accelerated through the use of advanced machine learning techniques to distinguish target-specific responses from non-specific binding events and electrode drift effects in complex, clinically-relevant fluids that most studies struggle to overcome. To demonstrate the effectiveness of the proposed approach, a biosensor platform for extracellular histone detection will be developed. The understanding that extracellular histones mediate tissue injury and propagate organ failure is relatively new, while the report of aptamer-based therapies is even more recent. Despite this, there have been no reports of electronic microsensors with targeted affinity for circulating histones. We therefore hypothesize that aptamer chemistry can be leveraged to functionalize the surface of potentiometric microsensors in order to perform early-stage, point of care (POC) detection of circulating histones, facilitate the identification of individuals at high risk for development of Multiple Organ Dysfunction Syndrome (MODS), and allow early treatment.

This project is sponsored by National Science Foundation (NSF).

Phase II IUCRC North Carolina State University: Broadband Wireless Access and Applications Center (BWAC)

Ismail Guvenc, Jacob James Adams, & Alexandra Duel-Hallen
09/15/2019 - 08/31/2023

The major goal of National Science Foundation’s Broadband Wireless Access and Applications Center (BWAC) lead by the University of Arizona is “advancing wireless technologies and providing cost-effective and practical solutions for next-generation (5G & beyond) wireless systems, millimeter-wave communications, wireless cybersecurity, shared-spectrum access systems, full-duplex transmissions, massive MIMO techniques, and others.” The North Carolina State University (NCSU) is planning to join NSF BWAC center starting in 2019 with at least four full industrial members. The addition of NCSU into BWAC will synergistically complement BWAC mission and vision, by introducing new and complementary research areas, including millimeter wave (mmWave) theory, circuits, antennas, and experimentation, drone based communications, visible light communications (VLC), antenna design for broadband communications, non-orthogonal multiple access (NOMA) and its variants, among other areas.

This project is sponsored by National Science Foundation (NSF).

A Fully Ultrasonic Approach for Combined Functional Imaging and Neuromodulation in Behaving Animals

Gianmarco Pinton, Omer Oralkan
09/01/2019 - 05/31/2022

Two very recent advancements have been transforming the field of medical ultrasound. First, the revolutionary discovery of ultrasound neuromodulation, which non-invasively targets and modulates activity in specific regions of the brain. Second, contrast-enhanced super-resolution, which can image microvessels at resolutions as small as ten microns, an order of magnitude smaller than the ultrasound diffraction limit, and at greater depths. To achieve this generational leap in performance super-resolution contrast imaging requires that tens of thousands of frames of data be rapidly acquired and analyzed, making this technique much more computationally and algorithmically intensive than standard ultrasound imaging. Furthermore, the skull presents a unique challenge because it aberrates and generates reverberations, which reduce the resolution detectability of contrast agents. Consequently, transcranial super-resolution imaging would be difficult if not impossible to translate to the brain in its current form with current clinical hardware, especially if 3-D imaging is desired (which it is for functional imaging). Combining ultrasonic neuromodulation with functional imaging relies on MRI to target the ultrasound focus and to assess the brain’s functional response. However, confinement in a magnet bore, which typically requires anesthesia and limits the range observable behavioral scenarios. Furthermore, fMRI is slow compared to the time scale of the neural response, which is on the order of tens to hundreds of milliseconds. There is a solution to these limitations, which our group proposes to achieve in this project by developing a fully ultrasonic approach that combines 3-D super-resolution functional imaging with neuromodulation in a single integrated ultrasound platform that can be used on behaving animals. Time reversal, in conjunction with a highly accurate acoustic simulation tool that we have developed, can correct for the aberrations induced by the skull morphology accurately focus ultrasound and improve detectability. New software and implementation approaches designed at UNC Chapel Hill, including our innovative adaptive multi-focus beamforming approach, will simultaneously target multiple regions of the brain and enable full 3-D volume acquisitions at volume frame rates over 5000 FPS, suitable for rapid (hundreds of milliseconds) functional imaging. Recent advances in ultrasound hardware will enable ultra-high frame rate processing. Our research team at UNC Chapel Hill is partnering with a world-leading transducer group at NCSU to develop a lightweight wearable neurostimulation array. Ultra-fast processors, large RAM buffers, GPUs, and high-bandwidth data transfer hardware will be utilized to handle challenging adaptive beamforming tasks and massive data acquisition. Our approach will be validated in partnership with Vanderbilt, who have been pioneering the field of neuromodulation in non-human primates. Our motivation is to develop an integrated ultrasound platform as a new approach for neurostimulation and blood flow-based functional ultrasound imaging in the whole brain, with a non-ionizing, non-invasive, low-cost technology that could be used for monitoring and modulation in behaving animals.

This project is sponsored by UNC - UNC Chapel Hill.

Development of Low-Power Electronics for ASSIST’s Self-Powered Adaptive Platform

Yaoyao Jia
09/01/2019 - 08/31/2020

In Year 8, this project mainly focuses on developing low-power electronics using commercial off-the-shelf (COTS) components for ASSIST’s Self-Powered Adaptive Platform (SAP). Two versions of SAP hardware prototypes will be developed in this project. More specifically, the major work regarding the development of the SAP hardware prototype will be developing the low-power circuit boards for ECG sensing, firmware programming the microcontroller unit (MCU) to enable the BLE data transmission and implement finite state control algorithms, and integrating the SAP hardware prototype into the current form factor (smart shirt). The main challenging of developing the SAP hardware prototype is how to reduce its power consumption to the target of

This project is sponsored by NCSU Advanced Self Powered Systems of Sensors and Technologies (ASSIST) Center.

EAGER: Curricula Development of a Quantum Programming Class with Hardware Access

Frank Mueller, Patrick Dreher, & Gregory T. Byrd
09/01/2019 - 08/31/2020

Quantum Computing (QC) has reached an early state of device maturity
with the availability of several hardware platforms and corresponding
programming environments. The potential of QC is significant as
algorithms, such as Shor’s prime factoring, have
the potential to break the barriers of classical complexity
classes and thus provide “quantum supremacy” for such algorithms.

We propose to create a curriculum for a quantum programming class with
access to cutting-edge quantum computing platforms. Specifically, we
propose to utilize cloud-based access to one gate-based platform and
one annealing-based platform to provide hands-on experience with
programming actual quantum hardware. Curricular material will include
the fundamentals in physics and mathematics required to understand
quantum computing, introductory material to the quantum field, and
programming environments for two cloud-based platforms. We also
propose to develop training material suitable for tutorials at major
conferences/symposia across different fields as well as online courses
for faculty, staff and students. As a means to gauge success, the
suitability of the material will be thoroughly evaluated statistically
via surveys at the end of educational units for both classes and tutorials.

This project is sponsored by National Science Foundation (NSF).

EAGER: Data-Driven Control of Power Systems Using Structured Reinforcement Learning

Aranya Chakrabortty
09/01/2019 - 08/31/2021

This proposal will generate new results on application of machine learning in power system controls.

This project is sponsored by National Science Foundation (NSF).

PAWR Platform Full Proposal: AERPAW: Aerial Experimentation and Research Platform for Advanced Wireless

Ismail Guvenc, Rudra Dutta, & Mihail L. Sichitiu
09/01/2019 - 08/31/2024

We propose AERPAW: Aerial Experimentation and Research Platform for Advanced Wireless, a first-of-its-kind aerial wireless experimentation platform to be developed in close partnership between NCSU, Wireless Research Center of North Carolina (WRCNC), Mississippi State University (MSU), University of South Carolina (USC), City of Raleigh, Town of Cary, Town of Holly Springs, North Carolina Department of Transportation (NCDOT), and numerous other project partners. With a major focus being on aerial communications within low altitude airspace, AERPAW will develop a software defined, reproducible, and open-access advanced wireless platform with experimentation features spanning 5G technologies and beyond. NCSU, USC, and MSU researchers have existing UAS experimentation capabilities and ongoing experimental research activities involving wireless technologies spanning software defined radios (SDRs), LTE, WiFi, ultra-wideband (UWB), IoT, and millimeter wave (mmWave), which will form the initial baseline framework for the AERPAW platform. To deploy AERPAW, NCSU will work closely with NCDOT’s Integration Pilot Program, a three-year FAA project that allows BVLOS UAS experimentation for medical supply delivery in North Carolina, in close collaboration with NCSU, several UAS companies, municipalities, and a medical institution. Initial flight tests have already started within the Raleigh area, and will be expanding to other parts of the state in 2019 and beyond. Any additional FAA permits, as necessary, will be secured by AERPAW team in close collaboration with NCDOT.

This project is sponsored by PAWR Project Office.

Potentiometric Detection of Neuropeptides for Non-Invasive Monitoring of Stress

Spyridon Pavlidis
09/01/2019 - 08/31/2020

The objective of this proposal is to demonstrate the detection of neuropeptide Y (NPY), a biomarker for stress found in human sweat, using gold-based potentiometric sensors that are compatible with ASSIST’s Health and Environmental Tracker (HET) 2.0 biochemical sensor architecture.

This project is sponsored by NCSU Advanced Self Powered Systems of Sensors and Technologies (ASSIST) Center.

SCH: INT: Collaborative Research: A Data-Driven Approach for Enhancing Wearable Device Performance – A Study on Early Detection of Asthma Exacerbation

Edgar J Lobaton, Alper Yusuf Bozkurt
09/01/2019 - 08/31/2023

Our main goals are to: (1) develop a statistically-sound data-driven framework for signal quality characterization of wearable devices in the real-world; and (2) use this framework for enhancing algorithmic developments and hardware design. Current approaches depend on rules or indicators derived from expert knowledge in controlled environments, so they do not generalize well to the use at-home. Our main application will be the early asthma exacerbation detection. We aim to employ the prototypes designed by the NSF-ERC ASSIST center, which aims to develop nano-enabled energy harvesting, energy storage, nanodevices and sensors to create innovative battery-free, body-powered, and wearable health monitoring systems.

This project is sponsored by National Science Foundation (NSF).

SMART SiC Power ICs Scalable, Manufacturable, and Robust Technology for SiC Power Integrated Circuits

Bongmook Lee
09/01/2019 - 08/31/2022

This collaborative project aims to develop scalable, manufacturable, and robust technology for SiC integrated circuits (SMART SiC ICs). To realize this goal, disruptive designs and processes will be developed to achieve integrated circuits of large scale (> 1 cm2) SiC Complementary Metal-Oxide-Semiconductor (CMOS) and high voltage (400 – 1200 V) lateral power MOSFETs (LDMOS) on 150 mm 4H-SiC substrates. The SMART SiC ICs will enable many applications requiring wide ranges of voltages and power ratings such as automotive, industrial, telecommunication, electronic data processing, energy harvesting, and power conditioning.

This project is sponsored by State University of New York (SUNY) - Albany.

Sub-15 μW Passive Radio for Self-powered Sensor Systems

David Ricketts
09/01/2019 - 08/31/2020

A low power radio for self-powered systems.

This project is sponsored by NCSU Advanced Self Powered Systems of Sensors and Technologies (ASSIST) Center.

Framatome – ECE Sr Design Fall2019-Spring2020 – Underwater Robot Blind Vision Recognition

Bobby Leonard Compton
08/29/2019 - 05/31/2020

Develop a means to detect objects that a robot encounters that cannot be visually seen by the operator thorough traditional camera means. Also, provide a means to notify the operator that the robot has encountered the unseen object.

This project is sponsored by Framatome.

Hanesbrand-ECE Sr Design Fall 2019-Spring 2020: NeverLost AutoAdjustable Kids Hoodie

Bobby Leonard Compton
08/29/2019 - 05/31/2020

A hoodie for kids that automatically adjust tension as well as provide a neverlost find feature through wireless networks to caregiver(s)/parent(s) mobile devices.

This project is sponsored by Hanesbrands, Inc..

Caterpillar BCP – Personnel and Object Avoidance System, ECE Sr Design Project Fall 2019-Spring 2020

Bobby Leonard Compton
08/21/2019 - 05/31/2020

A system to detect personnel and objects that is intended to be applied to industrial moving equipment

This project is sponsored by Caterpillar, Inc..

Duke Energy Carolinas, LLC Fall 2019 and Spring 2020 Project

Bobby Leonard Compton
08/21/2019 - 05/31/2020

An automated substation inspection robot

This project is sponsored by Duke Energy Carolinas, LLC (Duke Power).

Three Dimensional Study of the Benefits of Hybrid Bonding

Paul D. Franzon
08/16/2019 - 05/15/2020

NCSU will investigate the advantages of Hybrid bonding in 3DICs.

This project is sponsored by Xperi.

2D Hybrid Material Architectures for Terahertz (2D-HyMaTer)

Ki Wook Kim
08/15/2019 - 03/14/2023

Theoretical modeling of the proposed 2D/3D hybrid structure and its application to the hot electron transistors will be undertaken in close coordination with the experimental effort for accurate understanding and optimization of the performance. Considering the large mismatch in the vertical and lateral dimensions of the device, a hierarchical approach will be adopted for the analysis. In particular, an atomistic modeling based on first-principles density functional theory and non-equilibrium Green’s function methods will be pursued to describe hot electron dynamics in the emitter-collector junctions. Detailed information such as electronic structures, band offset, and tunnel barrier potential will be extracted as a function of layer thickness, stacking sequence, atomic termination, etc. A variety of material combinations will be explored for the hybrid structure with a focus on 2D nitrides. The impact of the defects will also be examined numerically.

This project is sponsored by Pennsylvania State University.

Direct Correlation Spectrometer and Solar Simulation Testbed for Research on Space Situational Awareness and Optical Communications

Michael Kudenov, John F. Muth
08/15/2019 - 08/14/2020

The requested equipment consists of various commercial off-the-shelf (COTS) components that will be assembled into an ultraspectral solar simulator testbed. The instrument can also be used as a high spectral resolution (Δλ ~ 0.004 nm or resolving power R = 137,500 at λ = 550 nm) monochromator or spectrograph. This testbed will serve as a platform for quantifying the performance of Fraunhofer line discriminators for luminescence and fluorescence detection, testing solar-blind imaging approaches, and for testing free-space optical communications systems or signaling methods.

This project is sponsored by US Air Force - Office of Scientific Research (AFOSR).

NSF Student Travel Support for the 27th IEEE International Conference on Network Protocols (IEEE ICNP 2019)

Wenye Wang
08/15/2019 - 07/31/2020

This proposal is to request travel funding for students at
U.S. institutions to attend the 27th IEEE International Conference on Network Protocols, Chicago, Illinois, USA, October 7-10, 2019.

This project is sponsored by National Science Foundation (NSF).

Spin Configuration, Chemical Reactions, and Synthesis under EM Field

Daryoosh Vashaee
08/15/2019 - 08/14/2022

This research covers a period of three years to accomplish two primary goals outlined herein. Implemented together, the two integrated components of this program are designed to impact the emerging field of electromagnetic field effects in materials synthesis and chemical reactions.
Aim 1: EM field interaction with Mott materials
Aim 2: Theoretical Modeling of the Non-thermal Microwave Effects and Experimental Tests

This project is sponsored by US Air Force - Office of Scientific Research (AFOSR).

Wearable Cerebral Oximetry

Alper Yusuf Bozkurt
08/09/2019 - 02/09/2021

Low burden and vigilant physiological monitoring of service members in the operational environment would provide better individual awareness and more actionable information for better planning by military decision makers. NIRSense proposes a wearable cerebral oximeter to directly monitor neural activity by measuring state changes in oxygenation of blood in the wearer’s prefrontal cortex.

This project is sponsored by NIRSense LLC.

RI:Small: Neural Architecture Search with Deep Compositional Grammatical Structures

Tianfu Wu
08/01/2019 - 07/31/2022

Explicit interpretability is largely missing in state-of-the-art computer vision and machine learning approaches, especially deep neural networks based methods. The goal of this project is to investigate principled methodologies of learning interpretability-driven models which address accuracy and transparency jointly. We focus on two domains under a unified framework: visual recognition (such as image classification, object detection and tracking), and agent autonomy in general game playing environments (such as ALS-Atari learning system and the Mario domain). We propose to integrate top-down image grammar models and bottom-up deep neural networks end-to-end. The proposed framework aims to rationalize prediction results (e.g., labels in visual recognition and actions in agent autonomy) by unfolding latent semantic configurations in visual inputs/states, i.e., sufficient statistics, in a weakly-supervised or self-supervised way. The project has three objectives. First, we will study a generic method which evaluates the post-hoc interpretability of any pre-trained model. Second, we will develop a novel interpretability-sensitive risk minimization method which learns interpretable models with end-to-end training. Finally, we will evaluate learned interpretable models qualitatively and quantitatively on both publicly available large-scale visual recognition benchmarks (such as ImageNet and COCO) and a proposed urban panorama benchmark for visual historians, and in intelligent game engine learning tasks.

This project is sponsored by National Science Foundation (NSF).

High Precision Measurements of Beta Decay Using Stored Ultracold Neutrons and Cold Neutron Beams

Albert R. Young, Paul R. Huffman, & Daniel D Stancil
07/15/2019 - 06/30/2022

This proposal covers measurements of neutron beta decay using a cold neutron beam at the Spallation Neutron Source and ultracold neutron (UCN) experiments at the Los Alamos National laboratory. The goal of these experiments are measurements which reduce the reduce the current uncertainties in the neutron lifetime to the level of about 1 second (the lifetime is 880 seconds in the latest average of the global data set) and the uncertainty in the axial coupling constant to about 0.025%. These quantities are important for high precision predictions of the energy output of the sun, the cross-sections for neutrinos coming from reactors and searches for physics beyond the standard model of particle physics.

Each experiment has unique strengths, in that Nab uses a cold neutron beam to provide an intense, localized source of neutrons, ideal for a time-of-flight spectrometer. The other two experiments, UCNA and UCNtau, use UCNs (neutrons going so slowly they can be stored in material vessels and magnetic traps) to help overcome systematic errors. The UCN measurements are stationed at the LANL UCN source, a solid deuterium source developed through earlier efforts co-led by our NCSU group.

This project is sponsored by National Science Foundation (NSF).

A Prototype DNA Hard Drive

Albert J. Keung, James Tuck
07/01/2019 - 03/31/2020

This proposal seeks to construct a prototype information storage system using dna.

This project is sponsored by NC Biotechnology Center.

Power America: Budget Period 5 Task 2.29 and 5.19

Philip Thomas Barletta
07/01/2019 - 06/30/2020

Task BP5-2.29: Implementation of SiC Block Process Steps to Aid Transition of SiC Technology Developments
With the support of PowerAmerica, X-FAB has established a 6-inch Silicon Carbide foundry line fully integrated within its 30,000 wafers/month silicon wafer fab. Due to its established reputation and full set of 6” SiC fabrication tools, X-FAB often receives inquiries from small organizations
that request small-batch SiC wafer processing. However, because of the small requested volumes, it is difficult to provide these companies access to the production capability of X-FAB. In order to service these requests, we propose to establish a small development fab with a set of standard process blocks in the NCSU Nanofabrication Facility (NNF). This would allow for an efficient
transfer into X-FAB’s production capacity from a more flexible University facility, as well as provide for development opportunity for next generation processes for SiC devices. This aligns with PowerAmerica’s larger strategy of providing companies access to SiC technology to accelerate innovation and adoption of SiC power devices in mainstream applications.

Task BP5-5.19: Development of Short Course for Wide Bandgap Power Devices in NCSU Core Facilities (Months 0-12)

Task Summary:

The NCSU Nanofabrication Facility (NNF) and Analytical Instrumentation Facility (AIF) will work together to develop a two-day short course which will explore the science and technology underpinning wide bandgap (specifically, GaN and SiC) power devices. The target participants for this short course will be professional engineers and technicians, specifically those working in the silicon field who are interested the wide bandgap technology. Both undergraduate and graduate university students will be welcome as well.

This project is sponsored by NCSU PowerAmerica: Next Generation Electronics Manufacturing Innovation Institute.

Strategic Design and Development of a Plant Bio-Mining System to Sustainably Harvest Rare Earth Elements from Domestic U.S. Sources.

Colleen J. Doherty, Michael Kudenov
07/01/2019 - 06/30/2022

Despite their abundance in US soils, REEs are dispersed and challenging to extract. The economic and environmental costs of extraction combined with the low resale value of REEs has resulted in decreased US production of REEs. The lack of US companies with the resources and interest in continuing to harvest REE generates a national security risk as the availability of these essential components is under foreign control. Current methods of REE extraction require the use of aqueous chemical treatments. New advances include the use of bacterial filters to capture REE. While these have contributed to reducing the cost of extraction, these approaches still require significant capital investment and a large amount of water to excavate and recapture the REE. Thus, these are approaches that can only be economically employed in areas with large deposits of REEs.
The successful completion of this proposed research will result in an economical plant bio-mining system to extract REE from soil and waste sources. The low costs and minimal footprint of the plant bio-miners will provide an efficient and scalable approach that can be deployed in areas ranging from small fields and consumer waste areas to large mines and reclamation areas. The low upfront costs will encourage the use of plant bio-miners thus reducing the scarcity of REEs and eliminating our dependence on foreign REE sources. The design and engineering of the plant bio-mining system will provide tools to understand how plants regulate uptake and distribute REEs and calcium, which REEs mimic. Small doses of REE can enhance tolerance to abiotic stress. The development of this system to accumulate REEs in plants will help us design REE-inspired treatments to mimic these positive effects on abiotic stress responses and enhance tolerance to drought and heat stress.

This project is sponsored by US Dept. of Interior (DOI).

Systems-level measurements of biophysical parameters in the Dorsal/NF-kappaB pathway

Gregory T Reeves, Cranos Williams
07/01/2019 - 06/30/2022

In the past decade and a half, our understanding of developmental biology has been revolutionized by real-time, live experimental approaches, which have acquired vast quantitative data sets and challenged established views of tissue patterning. It is now understood that gene expression does not simply rely on a steady state level of morphogen signaling, and thus, simple, intuitive descriptions of tissue patterning are no longer sufficient. To continue at the forefront of research, there must be a synergism of quantitative, real-time experiments, together with predictive computational models that synthesize the wealth of data into a coherent mathematical framework. However, it has been shown that such systems biology models have “sloppy parameters,” meaning there is a large ensemble of diverse parameter sets that each fit the noisy biological data sufficiently. This greatly reduces the predictive power of the models.
Therefore, the overall objective of this proposal is to perform detailed measurements of local biophysical parameters and global morphogen gradient properties to build and constrain a predictive, computational model of the Dorsal/NF-κB gradient in the early Drosophila embryo. During this stage, NF-kappaB signaling directs the formation of muscle, skin and neurons. Furthermore, the NF-kappaB pathway is highly conserved (i.e., the same) in all animals from flies to humans, making the lessons learned about NF-kappaB signaling in fruit flies directly relevant to human cancer research.
The central hypothesis is that such measurements, acting as model constraints, will greatly increase the model’s predictive power. Our hypothesis is based on our preliminary data and previous modeling experience of this pathway. Given that we also have experience in detailed measurements of this pathway, our lab has the capacity to perform this work. Only a few labs worldwide have combined both quantitative, real-time measurements with mechanistic models in the same system, which makes our lab nearly unique.
The expected outcomes of the work will be a more detailed understanding of the NF-κB module at the local and global level, as well as a model that can generate testable predictions. We expect these outcomes to have an important positive impact, because they will advance not only our understanding of the dynamics of Dorsal gradient formation, but the general field of biological modeling. Testing our central hypothesis will show whether models necessarily contain “sloppy parameters,” or may lead to discovering additional aspects that can improve the model. The proposed research will also our general knowledge of the NF-κB signaling module that can be found in animals from Cnidarians to humans.

This project is sponsored by National Science Foundation (NSF).

Contact-Free Heart Rate Monitoring from Video Under Motion

Chau-Wai Wong
06/25/2019 - 02/25/2020

The subcontract aims to rewrite software prototypes for heart rate monitoring from videos into software engineering grade computer programs. The grantee shall lead the development of software engineering grade computer programs that are written in reference to the software prototypes provided by the University of Maryland. The grantee shall provide feedback and suggestions to the University of Maryland to improve the software prototype.

This project is sponsored by University of Maryland, College Park.

ARO IPA: Program Manager, Processing and Fusion (Electronics Engineer)

Hamid Krim
06/24/2019 - 06/23/2021

An interest in a position at ARO in the capacity of an IPA contract employee is expressed. The interest is particularly focussed in exploiting the PI’s knowledge and familiarity with DOD challenges to provide the vision, leadership and help shape the research agenda priorities to ensure that the current as well future sensing and information and machine learning challenges be met.

This project is sponsored by US Army - Army Research Office.

Real-Time Remaining Useful Life Assessment for Batteries using the SBG at Butler Farm

Mo-Yuen Chow
05/16/2019 - 08/15/2019

The energy storage systems at Butler Farms are currently being monitored and maintained by NCEMC using the Smart Battery Gauge developed during the Smart Battery Gauge for Continuous Battery Assessment at Butler Farm and Smart Battery Gauge for Continuous Battery Health Assessment at Butler Farm projects. The Smart Battery Gauge was developed to continuously monitor and provide live feedback about the State of Charge and State of Health of the energy storage system at a rack level. This project will develop a Remaining Useful Life (RUL) Assessment algorithm to assist in determining State of Function (SOF).

This project is sponsored by NC Electric Membership Corp..

Feeder Anti-Islanding Detection Using HIL Modelling and Simulation

Mesut E. Baran, Srdjan Miodrag Lukic
05/15/2019 - 09/30/2019

This project will focus on hardware in loop analysis of faults within the feeder that uses the MATLAB/Simulink model of Mini D-VAR, Opal-RT software for HIL simulations.

The study will include using a feeder model and simulating different types of faults on the feeder and determining if for any of these faults, the protection and control logic implemented inside relays can potentially detect the fault, therefore not causing the creation of an island.

This project is sponsored by Duke Energy Business Services LLC.

Code-Modulated Embedded Test of Multifunctional Arrays

Brian Allan Floyd
04/26/2019 - 04/25/2024

We propose to investigate test solutions for millimeter-wave (mm-wave) arrays. A built-in-self-test technique called Code-Modulated Embedded Test (CoMET) has been introduced by NCSU which allows parallel extraction of individual array element’s amplitude and phase response. In this program, we will explore fundamental limits, extension of CoMET to new measurement classes, and benchmarking within manufacturing test environments.

This project is sponsored by Texas Instruments.

Economical Data-Fused Grid Edge Processor (EDGEPRO) for Future Distribution Grid Control Applications

Ning Lu, David Lee Lubkeman
04/01/2019 - 02/20/2022

The proposed concept entails the research, development, and demonstration of an economical, data-fused grid edge processor (EDGEPRO) that can generate required data to support flexible grid operations by processing raw data from various existing sources (e.g., smart transformers, smart pole-top sensors, distribution automation (DA) controllers, smart inverters). The edge device will process high-speed and high-volume data by leveraging data fusion and machine learning (ML) technologies, making and executing local grid control decisions, and communica-ting certain processed data with other control systems, the cloud, and/or the utility control center. Because of its capabilities, the EDGEPRO will be able to calculate “virtual meter” data that, will eliminateing the need for installing additional grid monitoring sensors and devices at many feeder locations such as a service transformer, to and reduce the overall cost of flexible grid control. The target cost for the advanced edge data processor is $3000 USD per unit.

This project is sponsored by ABB, Inc.

Next-Generation Non-Surgical Neurotechnology: Multifocal Integrated Non-Invasive Device for Sensing and Stimulation (MINDSS)

Omer Oralkan
04/01/2019 - 04/25/2020

In this project we will develop capacitive micromachined ultrasound transducer (CMUT) arrays for neurostimulation, capable of focused stimulation of a

This project is sponsored by Teledyne Scientific & Imaging, LLC.

Rugged WBG Devices and Advanced Electric Machines for High Power Density Automotive Electric Drives

John Victor Veliadis, Iqbal Husain, & Subhashish Bhattacharya
04/01/2019 - 03/31/2024

The objective of the project is to research, develop, and test GaN technology equipped lightweight electric motors for use in vehicle applications

This project is sponsored by US Dept. of Energy (DOE).

Towards Ultra-Reliable Low-Latency Communications for 5G UAV Ecosystems: Collaborative Research Planning among NC State, NU and AU

Shih-Chun Lin
04/01/2019 - 12/31/2019

As one of the 5G envisioned services, ultra-reliable and low-latency communications (URLLC) aim to provide secure data transmissions from one end to another with ultra-high reliability and deadline-based low latency requirements, enabling tactile Internet, mission-critical Internet of Things, and vehicle safety applications. Meanwhile, unmanned aerial vehicles (UAVs) for wireless communications has drawn much attention as the mass production of high-performance, low-cost, intelligent UAVs become more practical and feasible, which empowers more functional diversity for 5G networks. Based on the PIs’ expertise at the three institutions, Dr. Lin at North Carolina State University (NC State), Dr. Kobayashi at Nagoya University (NU), and Dr. Shi at The University of Adelaide (AU), this project will initiate collaborative research discussion and external grant planning for introducing a holistic software-defined wireless architecture that ensures URLLC in 5G UAV ecosystems. Several teleconferences and onsite discussion at three institutions will be established. The project will also organize an international workshop in the International Conference on Materials and Systems for Sustainability (ICMaSS) 2019 in Nagoya, Japan, to bring together researchers in all relevant areas. The PIs will actively seek the feedback from industry partners to work with us on developing, testing and deploying the 5G UAV framework. Moreover, PIs plan to develop a visiting/exchange Ph.D. student program designed to allow graduate students to spend a semester (preferably in summer) at the PIs’ institutions for academic exchanges to enhance the cross-linkage between the lines of research pursued by the team members.

This project is sponsored by Academic Consortium 21.

Information Sciences: Computing Science: Intelligent Systems: Tractable Deep Learning: Structure vs. Scale in Data

Chau-Wai Wong
03/28/2019 - 03/27/2022

Many well-established problems in data science, such as data classification and clustering, raise unprecedented challenges in presence of complex and high dimensional data. Our interest is in inference applications, and more generally analysis problems, which in turn often resort to representation theory. Our goal is to build on the many previous and more recent accomplishments in Machine Learning and data science to develop the tradeoff of structure versus deep scale when representing data for either feature characterization and exploitation or inference applications. The vast array of applications in data science we typically encounter, and of interest herein, invariably seek to glean/use an extensive number of features of the data, which may also invoke the scale information whose necessary depth, as in deep learning (DL), remains an open problem We propose to develop an analytical framework for deep structure understanding using the existing Deep Leaning development as a source of inspiration. We proposed to investigate the tradeoffs of structure versus depth, noted above , as well as the known and open challenges of DL, such as Universal Approximation Property, and convergence issues. We expect our resulting algorithmic development to hence present great advantages in relation to the state of the art, with equal or better performance, with predictable behavior.

This project is sponsored by US Army - Army Research Office.

Learning Novel Feature Representations from Deep Neural Networks (Image Deep Structure Learning and Inference Exploration)

Hamid Krim
03/21/2019 - 03/31/2021

This work is to thoroughly evaluate and test algorithms that have been developed within VISSTA Laboratory. These pursued remote sensing data sets with associated applications will strengthen our collaborative work with Lawrence Livermore by a number of internship periods of the student at LLNL.

This project is sponsored by Lawrence Livermore National Security, LLC.

Fusion Algorithm Development of Multi-Modality Data

Hamid Krim
02/25/2019 - 12/31/2021

Our goal in this effort is to apply recently developed multi-modality fusion algorithms to vehicle data collected at ORNL. The testing of additional sensors would ensure the applicability of our approaches to the ORNL target goal of potentially deploying these algorithms in their system which is an on-going project.
This testing project is to hence harness a number of sensing modalities including, acoustic, magnetic, video, possibly laser, and jointly exploit them to carry out target inference. We will focus on a vast database of vehicles most of which have been characterized by the previously mentioned modalities.
In coordination with the ORNL Project Lead, we will work to identify the potential stress factors for the developed algorithms in the field, and will define the proper strategies to preserve a robust or at least gracefully degrading performance of the algorithms.

This project is sponsored by Oak Ridge National Laboratories - UT-Battelle LLC.

CAREER: Reconfigurable Microfluidic-Microbalance Sensors to Monitor and Optimize the Performance of Microphysiological Models

Michael Daniele
02/15/2019 - 01/31/2024

Microphysiological Model (MPM) systems, i.e. organ-on-a-chip systems, are poised to revolutionize pre-clinical testing by predicting human response better than animal models. We will develop a Vascularization Monitoring System (VMS) which controls perfusion, while monitoring cell proliferation. The VMS will contain sensors for continuous monitoring of perfusion pressure, perfusion flow rate, and electrical impedance.

This project is sponsored by National Science Foundation (NSF).

CRII: SaTC: Secure Instruction Set Extensions for Lattice-Based Post-Quantum Cryptosystems

Aydin Aysu
02/15/2019 - 01/31/2021

The emergence of quantum computers poses a serious threat for existing cryptographic systems and necessitates deploying new encryption schemes relying on different mathematical principles to protect electronic devices in the post-quantum era of computing. While theoretical security of these systems are being thoroughly analyzed, attacks on their practical implementations are largely unexplored. The primary research goal of this project is to develop secure implementations for lattice-based cryptosystems—a major class of post-quantum encryption proposals. This work specifically addresses power and electromagnetic side-channel vulnerabilities on physical implementations of lattice-based cryptosystems that can extract secret information by observing its correlation to these computation effects.

To advance the understanding of secure lattice-based cryptosystem implementations, this project proposes a framework that uses instruction set extensions (ISEs) that is designed to mitigate power and EM side-channels and integrated into a customized processor which can map security-critical computations to the ISE. As a result, lattice encryption software can be composed from a set of secure hardware operations and the proposed framework can therefore be automated to secure and benchmark different lattice-based post-quantum proposals. The project will disseminate publications, open-source hardware and software, and it is targeted to bridge the computer architecture and hardware security research communities. This work will also help the ongoing post-quantum standardization effort in US.

This project is sponsored by National Science Foundation (NSF).

Evaluation of Novel Approaches for Early Detection of and Detailed Characterization of Maize Foliar Disease

Peter Ojiambo, Peter J. Balint-Kurti, & Michael Kudenov
02/01/2019 - 01/31/2020

We generally assess levels of foliar disease in corn by observation in the field using a visual scale. While this method is robust and gives reproducible data, it does not provide qualitative data such as lesion size or shape, nor does it give us good data on speed of disease progression or on timing of initial symptoms. We will rate a set of 50 genetically similar lines each of which has a different allele conferring resistance to the foliar disease southern leaf blight. We will use a variety of approaches to rate disease , including hyperspectral imaging and digital imaging. We will also rate them conventionally at very frequent intervals. Finally, we will measure yield.

This work will help to develop methods for the early detection of foliar disease in the field. It will also characterize disease progression and the relationship between symptoms and yield loss. This knowledge will aid in the development of predictive models to guide farmers in the decision of whether and when to apply fungicides.

The characterization of different mechanisms used by different resistance genes will guide breeders in the combination of resistance genes to produce more optimally-robust disease resistant lines.

This project is sponsored by Corn Growers Association of NC, Inc..

Learning Deep Grammar Networks for Visual Question Answering

Tianfu Wu
01/08/2019 - 12/31/2019

this proposal study deep grammar networks in visual question answering (VQA) tasks. In addition to publicly available VQA benchmarks, this project will also work on a new VQA dataset which has been created and are gradually scaling up through the Critical Events Project in the Visual Narrative Cluster at NC State University with which PI Wu is affiliated.

This project is sponsored by Salesforce.

PD-04: Development and Demonstration of a Power Electronics Assisted Distribution Voltage Regulator

Mesut E. Baran
01/02/2019 - 12/31/2019

This project aims at developing a novel power electronics assisted voltage regulator for the distribution grid. The proposed solution is based on the existing Step Voltage Regulator (SVR) but potentially increases their number of electrical operations by five times. The proposed solution offers arcless operation, fast dynamic response, volt/var control, and voltage sag/swell compensation capability.

This project is sponsored by UNC - UNC Charlotte.

Proposal DM-02: Identification and Mitigation of Coordinated Attacks on Distributed Energy Management, CAPER Core Project

Aranya Chakrabortty
01/02/2019 - 12/31/2019

This project will develop different cyber attack detection and mitigation scenarios for smart grid technology.

This project is sponsored by UNC - UNC Charlotte.

Adopting D-VAR to Mitigate PV Impacts on a Distribution System

Mesut E. Baran, Srdjan Miodrag Lukic
01/01/2019 - 12/31/2019

D-VAR is an emerging technology which is designed for distribution level volt/VAR applications. The goal in the first phase of the study is to quantify the benefits a D-VAR will offer for a given distribution feeder with high penetration of PV. The system that will be considered is a Duke feeder with large PV. Hence, the main focus of this study is to assess how effective mini D-VAR will be in mitigating these impacts on various distribution feeders in Duke Energy service territory.

The study will first simulate a given feeder to investigate the PV impacts on the circuit and then focus on the use of D-VAR to mitigate these issues.

This project is sponsored by Duke Energy Business Services LLC.

Collaborative Research: FORABOT: An Autonomous and Accessible System for Sorting Foraminifera

Edgar J Lobaton, Michael Daniele
01/01/2019 - 12/31/2021

Paleoceanography, among other research fields, depends crucially on ubiquitous ocean dwelling single celled organisms called foraminifera. Undergraduate workers are often employed to pick several thousands of specimens from ocean sediments for each study. Depending on deposition rates and abundance of the species, such manual processing can become tediously repetitive with little intellectual motivation for the undergraduate workers, and time and cost-prohibitive for research scientists. The proposed project aims to develop a completely autonomous system for visual sorting of foraminifera, which is accessible to the scientific community. This system will be compatible with existing off-the-shelf microscopes, it will make use of microfluidics in order to facilitate the transport of the samples from a container to their sorted receptacles, and will utilize machine learning for recognition. These tools will be made available to the entire scientific community, and aim to keep the fabrication cost under three thousand dollars.

This project is sponsored by National Science Foundation (NSF).

EIT Health Grant: SensUs 2019

Michael Daniele, Stefano Menegatti
01/01/2019 - 12/31/2019

As part of the 2019 SensUs Competition, the students and research of the team venture to design, construct and validate a sensor to detect and quantify biological medication for rheumatoid arthritis. SensUs provides SenseNC an opportunity to investigate a real-world issue in healthcare, while directly interfacing with the healthcare industry. These experiences will be valuable in current and future scientific endeavors for all team members.

This project is sponsored by TU/e.

Enabling Side-Channel Attacks on Post-Quantum Protocols through Machine Learning, CAEML Core Project P18-13 funded with industry membership dues

Aydin Aysu
01/01/2019 - 12/31/2019

This project is on using machine learning for trusted system design

This project is sponsored by University of Illinois - Urbana-Champaign.

Fast, Accurate PPA Model-Extraction, Center for Advanced Electronics through Machine Learning (CAEML) Core Project 3A2 funded with industry membership dues.

William R. Davis, Paul D. Franzon, & Dror Zeev Baron
01/01/2019 - 12/31/2020

This project researches methods for extracting fast and accurate estimators from System-Level Architecture to Power, performance, and area (SLA2PPA) in digital integrated circuits. Specifically, this project focuses on elimination of the complicated gate-level simulations needed to make accurate predictions of power, which typically occur very late in the design process. Extraction of system-level power models is extremely difficult, because the data-points are so few and so noisy, while the number of possible model parameters is so huge. This project will develop a comprehensive data-mining methodology to maximize the accuracy of PPA predictions while minimizing the data-collection effort.

This project is sponsored by University of Illinois - Urbana-Champaign.

High-Dimensional Structural Inference for Non-Linear Deep Markov or State Space Time Series Models, Center for Advanced Electronics through Machine Learning (CAEML) Core Project 3A4

Dror Zeev Baron, William R. Davis, & Paul D. Franzon
01/01/2019 - 12/31/2019

The project will explore deep Markov models for high dimensional time series. While past works on density estimation for multi-dimensional latent time series systems have focused on low- to medium- dimensional settings, we will try to move to higher dimensional settings.

This project is sponsored by University of Illinois - Urbana-Champaign.

An Innovative Secure Millimeter Wave (mmWave) Machine to Machine (M2M) Communication Network for Operating Drones

Ismail Guvenc, Huaiyu Dai
12/18/2018 - 09/30/2019

The use of Radio Controlled (RC) Unmanned Aerial Vehicles (UAVs) or Drones, for civilian and commercial purposes have been growing steadily for the past decade. Their non-military use range from responding to Hurricane Harvey to rescuing swimmers caught in 10-ft swells, and from pizza delivery to Prime Air, the Amazon drone delivery system. UAV’s have historically had a limited flight radius dictated by line-of-sight radio controllers; however, distance limitation from which the drone operator can control them can be bypassed by using commercial wireless networks to control the drone. It is expected that billions of 5G mobile and Internet-of-Things (IoT) wireless devices will be all connected with the new millimeter wave frequency bands. We propose to analyze and validate the hypotheses that 1) using mmWave with antennas tilted upward for RF coverage in the sky can lead to a secure and reliable wireless network for UAV/Drone operation, 2) there is a unique opportunity to use NOMA (Non Orthogonal Multiple Access) with the primary mmWave beam aimed towards a swarm of Drones to control them with high security and efficiency, 3) further increase security, reliability, and spectral efficiency by using co-operative communications among the swarm of Drones and 4) this swarm of drones can be effectively used for emergency recovery of critical infrastructure such as a cyber compromised power grid that requires a black restart.

This project is sponsored by Battelle Energy Alliance, LLC.

Evaluation of Sensor Technology for Real-Time Detection of Cyst Nematode Infected Soybean Plants

Ralph A. Dean, Omer Oralkan
12/01/2018 - 11/05/2019

Soybean cyst nematode (SCN, Heterodera glycines) is a major pest in all soybean-growing areas, particularly in sandy soils. Here, we propose a series of growth chamber experiments to demonstrate the potential of sensor technologies based on the capacitive micromachined ultrasonic transducer (CMUT) developed by our research team at NC State for detecting volatiles associated with SCN. In addition, we plan to identify and characterize discriminating VOCs from SCN infected soybeans and examine their detection by the sensor arrays.

This project is sponsored by BASF Corporation.

Fundamentals of Power Engineering to Support Integration of Distributed Energy Resources, CAPER Enhancement Project

Ning Lu, David Lee Lubkeman, & Mesut E. Baran
12/01/2018 - 08/31/2019

This project will develop course materials and instructor teaching aids to deliver a four-week course. The main goal of this course is to provide newly graduated engineering students and power professionals with a
quick but broad introduction on power engineering fundamentals related with the integration of distributed energy resources (DERs). This course materials will include fundamentals of power system design and operations pertinent to the adoption of DERs (e.g. energy storage, solar photovoltaics, controllable loads,
etc.) in power system operation and planning. Many engineering graduates today did not receive the necessary training on the basics of three-phase electric power because most universities no longer require power systems be taken by all electrical engineering students. This course will cover basic topics usually
taught in a two-semester elective power engineering curriculum. After taking this condensed course, engineers with a general engineering background will be equipped to master the following fundamental materials on how to operate and plan a three-phase electricity power system: the modeling of power
system components, power flow studies, economic dispatch, unit commitment, power system dynamic response, the modeling of microgrid and DERs.

This project is sponsored by Clemson University.

2019 International RoboSub Competition

John F. Muth
11/15/2018 - 08/31/2019

The underwater robotics club competes in the AUVSI RoboSub competition, an international robotics competition sponsored by the Association for Unmanned Vehicle Systems International and the US Office of Naval Research. In RoboSub, teams compete to create Autonomous Underwater Vehicles (AUVs) that can navigate an obstacle course and complete tasks underwater with no human input whatsoever. The tasks are designed to be similar to the real world, such as searching for and retrieving objects on the floor of the pool, manipulating levers and wheels, avoiding obstacles, and locating an acoustic “pinger” (sonar transmitter), much like the ones that are used to locate the “black box” on downed airplanes. Every year, students from roughly 40 teams around the world decide to take this challenge upon themselves, and learn real engineering, problem-solving, and teamwork skills along the way.

This project is sponsored by NCSU NC Space Grant Consortium.

Three-Phase T-Type Inverter

Subhashish Bhattacharya
11/06/2018 - 12/09/2019

Initially introduced to mitigate losses in medium voltage drives, the development of Wide Bandgap (WBG) semiconductors have now made multilevel inverters a viable alternative to the conventional two level inverter at low voltages also. The benefits of multilevel inverters over two-level inverters are given below:
1. Reduction of voltage transients at the motor windings
2. Lower harmonic distortion in the output current and voltage
3. Reduction in output filter size
4. Lower common mode currents
5. Reduced stresses on the power switches
The Three-Phase T-Type Multilevel Inverter in specific offers superior performance, with the conduction losses of a two-level inverter and the switching losses of a three-level inverter. These advantages allow the T-Type inverter to be operated at very high switching frequencies, making them ideal for high-speed motor drives. Also, the lower THD in output current produces less torque ripple, making them suitable for high precision servo drives.

This project is sponsored by Lockheed Martin Corp..

Grid-forming Battery Energy Storage System Characterization and Testing

Srdjan Miodrag Lukic
11/01/2018 - 08/01/2019

The goal of this project is to study the loading capabilities of an inverter operating in grid forming mode. A Battery Energy Storage System (BESS) may need to power up a microgrid after an outage, thus supplying all of the magnetizing currents to line-start machines as well as isolation transformers in the microgrid. There is a need to understand the capabilities of the state-of-the art BESS inverters to support all of these loads. Though simulating such behavior is feasible, experimental validation is required to guarantee that the system will operate as expected, and the BESS inverter protection will not trip.

This project is sponsored by Duke Energy Business Services LLC.

Tunable RF to Millimeter-Wave Receivers and Filters

Brian Allan Floyd
10/25/2018 - 07/24/2020

We will investigate architectures for frequency-selective receivers which can be tuned over a wide frequency range (18-50GHz). These will exploit properties of n-path passive mixers and frequency-selective feedback. Prototypes will be created in advanced SOI CMOS technology.

This project is sponsored by Air Force Research Laboratory (AFRL).

FoMR: Post-Silicon Microarchitecture

Eric Rotenberg
10/01/2018 - 09/30/2021

This project explores new ways to exploit field-programmable hardware (FPGA) building blocks when they are co-mingled within and among the pipeline stages of high-performance microprocessor cores. In particular, the PI addresses the topics called-out in the FoMR RFP under: “Utilization of new microarchitecture building blocks, such as reconfigurable logic to boost IPC”.

This project is sponsored by National Science Foundation (NSF).

Intelligent, Grid-friendly 1MVA Medium Voltage Extreme Fast Charger

Srdjan Miodrag Lukic, Kenneth Allan Dulaney, & Iqbal Husain
10/01/2018 - 12/31/2021

North Carolina State University (NCSU), ABB, and New York Power Authority (NYPA) will develop and demonstrate an intelligent, medium voltage (MV) extreme fast charger with integrated generation and storage capabilities that will help avoid negative impacts of extreme fast charging on the nation’s electric grid. The charger will be capable of delivering a combined 1 MVA to five vehicles, while enabling a charge rate of up to 350 kW per stall. The system will consist of a solid-state transformer (SST), which connects directly to the medium voltage (MV) and delivers power to a shared, 1,000 V DC bus, to which multiple vehicles, generation (PV), and storage units can be connected through partial-power DC/DC converters. The DC bus will be protected using novel intelligent solid-state circuit breakers, developed by ABB for this effort. Each vehicle will interface to the DC bus through a correctly sized DC/DC converter, allowing charging in the 50 kW to 350 kW range at the vehicle battery voltage. Therefore, this station will be capable of supporting state-of-the-art electric vehicles as well as the next generation of vehicles operating at higher voltages and faster charging rates.

This project is sponsored by US Dept. of Energy (DOE) - Energy Efficiency & Renewable Energy (EERE).

NeTS: Small: Collaborative Research: Improving Spectrum Efficiency for Hyper-Dense IoT Networks

Ismail Guvenc
10/01/2018 - 09/30/2021

The emerging Internet of things (IoT) technologies will enable a whole new set of applications, imposing far reaching influences on multifarious aspects of the society. At the same time, the new and non-traditional deployment scenarios for the IoT technologies also pose several grand challenges that need to be addressed for their successful operation, including but not limited to: 1) complex and dynamic interference characteristics due to unplanned and massive IoT deployments; 2) self- and other-user interference problems due to utilized carrier waveforms, strongly coupled to each other due to massive deployment scale; and 3) scarcity of existing spectrum resources for supporting large number of simultaneous IoT links. In this proposal, the PIs will develop novel physical (PHY) and medium access control (MAC) layer IoT architectures and algorithms to enable cognitive interference management for massively deployed IoT technologies, and evaluate the proposed designs on software defined radio (SDR) based experimentation platforms. A comprehensive study into stochastic geometry based capacity analysis, joint equalizer and waveform designs, and graph based radio resource management will be pursued and treated in an integrated manner.

This project is sponsored by National Science Foundation (NSF).

SpecEES: Efficient Monitoring and Spectrum Utilization of Multi-Layer Wireless Networks

Wenye Wang, Do Young Eun, & Huaiyu Dai
10/01/2018 - 09/30/2021

The practice and experience in more than a decade have demonstrated that spectrum sharing is difficult: opportunistic spectrum access by secondary systems has a major technical hurdle it is difficult to
accurately sense the spectrum band status and detect a new primary signal while the secondary communication is ongoing. At the same time, it is factual that we have many existing and upcoming wireless access technologies, which have an acute demand for spectrum sharing and better utilization than today. We believe that the current difficulty to realize the full potential of radio spectrum is due to the binding of a wireless service to a specific radio spectrum. In other words, most of the prior studies focused on algorithms and protocols to improve spectrum efficiency, but paid less attentions to how these solutions will eventually benefit the users. With today’s huge number of wireless devices and ever-increasing new wireless services, we need a new paradigm to separate wireless services from radio spectrum, so that the radio spectrum is abstracted and mapped to a wireless service only when it is needed, rather than a static binding for years. Therefore, we propose to study a Multi-Layer wireless networks in the sense that each access technology being a radio layer, and each wireless device being able to user multiple wireless interfaces for opportunistic access. Our objective is to build a theoretical framework that stemming from detecting and identifying radio spectrum in a geographical region, to selecting an optimal access band or channel from an individual device’s perspective, and further to achieve rendezvous with common channels for pair-wise communications, and eventually building device-to-device communications via single-hop and multi-hop networking architecture.

This project is sponsored by National Science Foundation (NSF).

NSF Workshop on Reconfigurable Sensor Systems Integrated with Artificial Intelligence and Data Harnessing to Enable Personalized Medicine

Michael Daniele, Veena Misra
09/15/2018 - 08/31/2019

The focus of this multi-phased workshop is to determine future strategies for advancing the fundamental understanding and engineering of reconfigurable sensor systems by integrating hardware with data harnessing, real-time learning, and artificial intelligence capabilities. Specifically, this workshop will define the state-of-the-art, necessary innovations, and future challenges facing the research and development of reconfigurable sensor systems for applications in understanding of human physiology, pathophysiology, metacognition, cognition, and behavioral psychology.

This project is sponsored by National Science Foundation (NSF).

CPS:Medium:Multimodal Sensing for Early Detection and Real-Time Correction of Water Stress and Nutritional Needs in Plants

Michael Daniele, Alper Yusuf Bozkurt, & Edgar J Lobaton
09/01/2018 - 08/31/2021

Recent developments in miniature, low-power wireless sensors has provided systems capable of long-term deployment and continuous operation. Plant sciences will be benefited by the application of such a tailored suite of sensors, in which the output data will inform real-time changes to growth conditions in order to minimize cost and maximize yield. This proposal develops a physical and computational framework that will determine the necessary suite of plant physiology sensors and uses the collected data to model the complex interactions between phenotypical response and growth conditions. The contributions of this award will facilitate the broad adoption of new plant physiology sensors and analytic platforms for plant/crop management.

This project is sponsored by US Dept. of Agriculture (USDA) - National Institute of Food and Agriculture.

Leverage Augmented Reality for Safety Education in the Logistics Industry

Xu Xu, Karen Boru Chen, & Jing Feng
09/01/2018 - 08/31/2021

In the next ten years, the annual growth rate of the U.S. logistics industry is expected to be 7.1%. The rapid market growth highlights the increasing need in supporting education of the future logistic workforce. Technology, such as automation and mobile computing, is evolving in the logistics industry, which results in a decline of human workers. Yet, complete automation in the last-mile delivery remains challenging due to the environment being less structured and predictable. Thus, many believe human workers will remain in the loop to react to unanticipated scenarios.

In partnership with the Ergonomics Center of North Carolina, the goal of this cyberlearing effort is to design and develop an immersive and personalized educational approach by exploring augmented reality (AR) to support workers’ understanding of risk factors associated to their work, and encourage workers to perform tasks using appropriate body movements. Specifically, we will focus on delivering knowledge on the low back and shoulder injuries, as injuries of those two body regions are the most common in logistics industry.

This research will promote workplace health and safety minimizing the risk of work-related injuries. One of the immediate applications is providing body motion training to the workers of material handling tasks of which the prevalence of low back injuries remains high. The knowledge gained in mechanics quantity visualization in augmented environment also can be immediately applied in K-12 education of physics as well as college level biomechanics courses. In the long-run, this research will also advance studies related to motor learning, such as sports training and tele-rehabilitation.

This project is sponsored by National Science Foundation (NSF).

Planning Grant: Engineering Research Center for Rapid Innovations in SystEms Engineering and Agricultural Sustainability (RiseEnAg)

Cranos Williams, Michael Kudenov, & Rosangela Sozzani
09/01/2018 - 08/31/2019

We propose this planning grant to fund activities that will crystallize the engineering research theme and further define the research thrusts that are needed to accomplish the targeted societal impact of the Engineering Research Center for Accelerating Agricultural Sustainability from Seed to Table. This Engineering Research Center proposes integrative systems solutions and innovative strategies that will address the challenges associated with food security in the 21st century. We anticipate that the engineering solutions and decision support systems that are developed as part of this ERC will accelerate the discovery breeding and management strategies for increasing crop yield under current resource constraints and enhance crop robustness to minimize losses that occur at various stages of the food supply chain. The ERC will have four synergistic research thrusts: 1) Sensor Development, Calibration, and Integration; 2) Data Mining, Machine Learning, and Multiscale Modeling for Improving Plant Yield, Robustness, and Development; 3) Heterogenous Testbeds for Inducing and Monitoring Complex Growth Conditions; and 4) Data Management Cyberinfrastructure and High Speed Computing Architecture Development.

This project is sponsored by National Science Foundation (NSF).

PV Inverter Systems Enabled by Monolithically Integrated SiC based Four Quadrant Power Switch (4-QPS)

Subhashish Bhattacharya, B. Jayant Baliga, & Douglas C Hopkins
09/01/2018 - 12/31/2021

This work brings together three innovations: Newly developed 4-Quadrant Single Die SiC-JBSFET based Power Semiconductor Switches (4-QPSs) are used to enable a new breed of Power Conversion Systems (PCS) for photovoltaic (PV) applications based on a cyclo-converter topology, and that are combined into two new module packaging schemes for creation of ultra-high density, low cost power conversion cells. Novel DC/AC power converter topologies leveraging high frequency (HF) transformer technology coupled with SiC based 4-QPS are proposed for commercial and household PV inverter applications. This combined technology development of the scalable power converter cell as a building block from the monolithic 4-QPS device die, package and converter will meet and exceed the higher efficiency, power density, specific power and relative cost metrics envisioned in the FOA. This is specifically done by innovative implementation of a SiC based 4-QPS based on monolithically integrated die which can be scaled up in current and voltage due to majority carrier characteristics. Innovative module packaging provides integration of bidirectional 4-QPS to construct power converter cells to achieve higher efficiency, power density and specific power metrics as required by the FOA. The proposed topologies can be designed to satisfy all current and emerging interconnection, interoperability, and grid support functional requirements while also achieving a combination of increased efficiency, power density, reliability, and reduced costs as compared to conventional solar inverters. The proposed module offers flexible integration of multiple types of Distributed Energy Resources including Energy Storage, Fuel Cells, and Responsive Loads on the PV plant side for optimized delivery of power to the grid. Prototype hardware will be demonstrated at power levels and voltage ratings relevant for commercial scale installations up to 50 kW using (1) newly developed SiC based 4-QPS devices (2) custom packaging of the 4-QPS (3) HF transformer technologies based upon state-of-the-art commercial magnetic cores. Simulation studies will also be performed in parallel to demonstrate the advanced grid-support features enabled by the proposed topologies. The proposed concepts leverage many recent investments and capabilities established through PowerAmerica Semiconductor Power Device Electrical Characterization Station, the NCSU FREEDM Center, X-Fab Foundry, NCSU Designed Foundry Process Developed at X-Fab, NCSU Laboratory for Packaging Research in Electronics Energy Systems (PREES) amongst others. The project scope and teaming structure seeks to transition the technologies under development to major US manufacturers to accelerate commercialization and enable successful realization of broader deployment of affordable and reliable PV-based generation throughout the US energy infrastructure.

This project is sponsored by US Dept. of Energy (DOE) - Energy Efficiency & Renewable Energy (EERE).

Interdisciplinary Distinguished Seminar Series

Tianfu Wu, Hamid Krim
08/22/2018 - 08/21/2021

Fundamental problems in science and engineering have become increasingly interdisciplinary, requiring knowledge and expert input from several areas of research. This is both challenging and exciting. The primary challenge faced by researchers is to keep abreast of new developments in tangential research areas to their own, not to mention those which are considered different. The increasing complexity of newly arising problems has on the other hand, invariably required a multifaceted approach to viewing and understanding them, and ultimately produce a solution. To that end, the PIs propose to host a regularly scheduled seminar series with preeminent and leading researchers in the US and the world, to help promote North Carolina as a center of innovation and knowledge and to ensure safeguarding its place of leading research.

This project is sponsored by US Army - Army Research Office.

ECE Senior Design Projects for ARO in 2018-2021

Rachana Gupta
08/20/2018 - 08/19/2020

Multiple NCSU ECE students teams will be working on multiple Senior Design projects during the period between 2018-2021. Army Research Office will provide multiple project descriptions suitable for the senior design course projects. Multiple projects will be offered and assigned during Fall and Spring semesters during this period. Students will not receive any funds from the sponsored project for this effort other than travel reimbursement when applicable.

This project is sponsored by Applied Research Associates, Inc. (ARA).

A Testbed to Study Interactions of PV Installations with Distribution Systems

Srdjan Miodrag Lukic, David Lee Lubkeman
08/16/2018 - 08/15/2019

The objective of this project is to construct a testbed and analysis framework for investigating how large PV penetration on a feeder affects the operation of the distribution system. In recent years, as the number of solar installations has increased, utilities have experienced unexpected power system behavior near the solar installations. These issues result from interactions between PV inverters and/or between the PV inverters and utility equipment such as transformers, breakers and capacitor banks. Since the inverters that interface the solar panels to the grid operate at switching frequencies in the kHz range, the available data recordings may not provide the fidelity required to find the root cause of the problem. Further, the placement of data acquisition equipment may not supply the required information for a complete understanding of the root cause of a problem.

This project is sponsored by Duke Energy Business Services LLC.

Smart Battery Gauge for Continuous Battery Health Assessment at Butler Farm

Mo-Yuen Chow
08/16/2018 - 08/15/2019

The energy storage systems at Butler Farms are currently being monitored and maintained by NCEMC using the Smart Battery Gauge developed during Phase I of this project. The Smart Battery Gauge was developed to continuously monitor and provide live feedback about the State of Charge of the energy storage system at a rack level. This project will develop a State of Health (SOH) estimation algorithm that can provide meaningful insights into appropriate energy storage system operation in the microgrid to increase Remaining Useful Life (RUL) and State of Function (SOF).

This project is sponsored by NC Electric Membership Corp..

Wide-Area Control of New York State Power Grid using FACTS and Wind Farms, FREEDM Core project

Aranya Chakrabortty
08/16/2018 - 06/30/2020

The objective of this research will be on improving dynamic performance of New York State (NYS) power grid using supplementary Wide-Area Damping Control (WADC) with shunt-connected FACTS devices and Wind farms as the control actuators. The NY state is moving towards more renewable generation. The state of New York already undertaken a comprehensive energy strategy, known as Reforming Energy Vision (REV), for building a clean, more resilient, and affordable energy system. One of the major goals of REV is to reach 50% renewable generation by the year 2030. Bulk wind power integration will be a major contributor in reaching this goal. Different research conducted by New York Power Authority (NYPA) and FREEDM Systems Center have shown that high wind penetration can impact the grid oscillation properties adversely and can induce poorly damped inter-area oscillatory modes. This could result in destabilization of the power grid. In wake of this scenario, NYPA is considering to implement Wide Area Controllers within their territory. NYPA has already installed multiple Phasor Measurement Units (PMUs) all across the grid. Currently, data stream from PMUs is being used to provide Wide-Area Situational Awareness (WASA) for the system operators; however, this data is not being used for any decision making and control-based remedial action for grid operation. Recently more emphasis is given to use this Wide-Area Measurement Systems (WAMS) in order to design oscillation damping controllers. This research will look into explore the feasibility, constraints and possible solutions for the real-life implementation of wide-area damping controllers through FACTS and Wind farms in New York State Grid.

This project is sponsored by NCSU Future Renewable Electric Energy Delivery and Management Systems Center (FREEDM).

EAGER: RF Switches Using 2D Phase Change Materials

Spyridon Pavlidis
08/15/2018 - 01/31/2020

Supplemental funds to support research experiences for undergraduates (REUs) are sought. These undergraduates will participate in the development of synthesis and characterization tools for 2D phase change materials.

This project is sponsored by National Science Foundation (NSF).

Polymer Semiconductor Focal Volume Arrays for Advanced Multidimensional Imaging

Michael Kudenov, Brendan Timothy O'Connor, & Michael James Escuti
08/15/2018 - 07/31/2021

This proposal will develop the first semi-transparent 3-dimensional (3D) volumetric imaging array by leveraging the unique advantages offered by emerging organic photovoltaic (OPV) detectors. These new detector-based degrees of freedom will enable an extra dimension onto which information can be modulated, enabling more compact, robust, and capable optical imaging sensors and systems. Organic semiconductors are advantageous to realize this concept due to their ability to tune transmittance, polarization sensitivity, and spectral response, enabling detector placement arbitrarily within a lens system’s focal volume. These new degrees of freedom will be used to investigate new detector capabilities, optical systems, and image processing algorithms. The objectives of this proposal are to: (1) Establish an optical model of both 2D and 3D polarization sensitive organic photodetector (P-OPD) arrays; (2) Design a proof of concept 2D and 3D P-OPD arrays and readout circuitry; (3) Leverage the model to optimize spectral- and polarimetric- imaging array using birefringent filtering techniques; (4) Create algorithms for image reconstruction and calibration; and (5) Incorporate methods to create multi-layer volumetric 3D P-OPD arrays with liquid crystal layers.

This project is sponsored by National Science Foundation (NSF).

Proof-of-Concept Study for Integrated Patch Recorder for Fetal Health Monitoring

Michael Daniele, Edgar J Lobaton
08/15/2018 - 08/14/2020

Proof of concept investigation for the engineering of novel acoustic-based fetal heart rate monitors.

This project is sponsored by Easton Technologies, LLC.

FoMR: Post-Silicon Microarchitecture

Eric Rotenberg
08/01/2018 - 07/31/2021

This project explores new ways to exploit field-programmable hardware (FPGA) building blocks when they are co-mingled within and among the pipeline stages of various general-purpose core types, including superscalar cores, wide-vector cores, and trace processors. In particular, the PI addresses the topics called-out in the FoMR RFP under: “Utilization of new microarchitecture building blocks, such as reconfigurable logic to boost IPC”.

This project is sponsored by Intel Corporation.

PFI-TT: Development of Single-Stage Power Modules for Modular Medium-Voltage Electric Vehicle Fast Chargers

Srdjan Miodrag Lukic, Iqbal Husain, & Srdan Srdic
08/01/2018 - 01/31/2020

We propose a next generation high-performance isolated medium-voltage (MV) building block for electric vehicle (EV) dc ultra-fast charging and other MV rectification applications. This work builds on the efforts to develop a solid-state transformer as a part of the NSF FREEDM Engineering Research Center. The main innovation is in the design of the high-performance isolated single-stage converter that combines a power factor correction and an isolated dc/dc conversion stage. The motivation for this work is to more efficiently serve the growing demand for dc fast and ultra-fast recharging infrastructure for EVs by significantly reducing the recharging time and bringing a gas station-like experience to the EV users. Coming from Future Renewable Electric Energy Distribution and Management (FREEDM) Systems Center (an NSF-funded generation-III Engineering Research Center), the team will build on their previous experience in MV systems to develop a 35 kW MV EV fast charger building block using this unique technology. The team aims to transfer the developed technology to the marketplace by employing market research and customer discovery strategies learned in the first Cohort of the newly formed NCSU NSF I-CorpsTM Site.

This project is sponsored by National Science Foundation (NSF).

VOC for digitally-enabled early remote sensing of Fusarium Head Blight

Ralph A. Dean, Omer Oralkan, & Yeon Oh
08/01/2018 - 07/31/2019

The overall goal of this project is to develop, test and fabricate a multi-element CMUT sensor that can selectively detect VOCs produced in real-time during early infection of wheat heads by Fusarium graminearum.

This project is sponsored by BASF Corporation.

Learning Deep AND OR Grammar Networks for Object Tracking, Detection and Parsing: A Unified Framework

Tianfu Wu
07/02/2018 - 07/01/2021

The objective of this project is to develop a unified framework of learning deep AND-OR grammar networks (AOGNets) for object tracking, detection and parsing, which has the following capabilities: (i) Harness both the explainable rigor of top-down hierarchical and compositional models and the discriminative power of bottom-up deep feature extractors in an end-to-end learning framework, thus learn actionable information for object tracking-by-detection-and-parsing and object detection-and-parsing-by-tracking; (ii) Address the inherent data-scarce challenge rigorously in online object tracking, detection and parsing (e.g., only one shot with ground-truth label available in initialization), thus handle small-data-for-big-task in contrast to big-data-for-small-task with deep neural networks. (iii) Tackle learning-to-learn or scheduling-for-learning to scale up both object tracking-by-detection-and-parsing and object detection-and-parsing-by-tracking in an effective and efficient way, thus showcase continual learning without catastrophic forgetting.

This project is sponsored by US Army - Army Research Office.

Acoustic Angiography Using Dual-Frequency and Ultrawideband CMUT Arrays

Omer Oralkan, Paul A. Dayton, & Feysel Yalcin Yamaner
07/01/2018 - 03/31/2022

Recent research has demonstrated that the performance of contrast enhanced ultrasound imaging in resolution and signal-to-noise ratio can be enhanced substantially with broadband dual-frequency transducers which can enable superharmonic ‘acoustic angiography’ contrast imaging. Data have demonstrated that this new imaging paradigm can detect biomarkers of cancer with substantially higher sensitivity and specificity than traditional grayscale ultrasound. The main limitation is that such transducers are very difficult to fabricate, however, our team believes that Capacitive Micromachined Ultrasonic Transducers (CMUTs) may be the answer to this challenge. In this project, we will design and test CMUTs for broadband dual-frequency contrast ultrasound imaging.

This project is sponsored by National Institutes of Health (NIH).

Bioelectrical Monitoring of Date Palm Tree Health For Early Detection of Red Palm Weevil Infestation

Alper Yusuf Bozkurt
07/01/2018 - 06/30/2020

We will develop a microelectronics platform system to better understand the phenotypic expression of stress on palm trees and its relation to plant injury and red palm weevil (RPW) infestation. This is an interdisciplinary project integrating fabrication of sensors and wireless front- and back-end circuits to monitor and protect palm trees from RPW.

This project is sponsored by King Abdullah University of Science and Technology (KAUST).

Fellowship for Graduate Student Sariful Islam Working on FREEDM Core Project Entitled “Next Generation Lightweight Electric Machines”, FREEDM Enhancement Project

Iqbal Husain
07/01/2018 - 06/30/2020

The objective of this project is to develop lightweight electric machines through a combination of approaches and explore the opportunities and challenges.

This project is sponsored by ABB, Inc..

FREEDM Electric Machines and Drives Research, FREEDM Core Project

Iqbal Husain
07/01/2018 - 06/30/2020

Electric machines and drives are a central area of research for FREEDM and are supported by our industry members.

This project is sponsored by NCSU Future Renewable Electric Energy Delivery and Management Systems Center (FREEDM).

LSAMP BD: North Carolina State University Preparing Researchers of the Future (PROF) NC-LSAMP

Warwick A. Arden, Roy Anthony Charles, & Ashleigh Renee Wright
07/01/2018 - 06/30/2020

The North Carolina Louis Stokes Alliance for Minority Participation (NC-LSAMP), requests a supplement to implement Cohort VII of the “Bridge to the Doctorate” program with North Carolina State University (NC State) serving as the institutional site. NC State University is a member since the beginning of the North Carolina Louis Stokes Alliance for Minority Participation. As one of the two flagship research universities in the University of North Carolina Education System, NC State’s world leadership in research and education makes it an ideal site for this phase of the NC-LSAMP Bridge to the Doctorate program. NC State university proposes to support a critical mass of 12 Bridge to the Doctorate fellows in each of the two years of this program. We have a firm written commitments from senior NC State University leadership in the College of Engineering and College of Science, to guarantee funding for BD Fellows through completion of their Ph.D. degree. We plan to develop new initiatives that will increase the percentage of BD fellows that complete their doctorate. Our proposed initiatives will help recruit, retain, and prepare researchers of the future in STEM beyond the timeline of this BD program and change the culture at NCSU for underrepresented graduate students in STEM. At NC State University, our goals are 1) to broaden participation of underrepresented students pursuing a graduate degree, 2) to improve graduate student mentoring and develop a Presidential style advisory panel structure for each student, and 3) to provide workshops on research methods and transition from undergraduate to graduate school for graduate students.

This project is sponsored by National Science Foundation (NSF).

Monitoring RPW Infestation Using Thermal, Hyperspectral and Novel Tracking Techniques

Alper Yusuf Bozkurt
07/01/2018 - 06/30/2020

In this project, we undertake a multi-disciplinary approach, exploiting both remote and in-situ sensing, to identify the potential of these emerging technologies for the early detection of the Red Palm Weevil. Unmanned Aerial Vehicles (UAVs) will be deployed as a mobile and adaptable delivery sensing platform, leveraging their unique characteristics to monitor from tree to plantation scales using specialized sensors. Imagery will be collected through a controlled experiment that seeks to monitor both healthy and infested trees, providing the basis for imagery analysis using machine learning, data integration and related analytical approaches. We will leverage this areal platform with the deployment of ground-based, but wirelessly connected, animals in the field. Through the development of electronic wearables, UAVs will be able to “sense” animals in real time, providing information on their location, biometrics (heart and respiratory rate) and behavior as an indicator of RPW infestation and to inform search and detection outcomes.

This project is sponsored by King Abdullah University of Science and Technology (KAUST).

Power America Pavlidis Task BP4-5.17 Graduate Wide Bandgap Semiconductor Device Lab

Spyridon Pavlidis
07/01/2018 - 09/30/2019

The objective of this proposal is to establish a graduate-level laboratory course in the school of Electrical and Computer Engineering at North Carolina State University that will provide students with hands-on
experience fabricating and electrically testing wide bandgap semiconductor power devices. The teaching material generated for this course will also be made available to PowerAmerica to facilitate the adoption of new wide bandgap semiconductor device courses in partner universities. Unlike traditional
semiconductor device and IC fabrication courses, this course will not focus on silicon CMOS technology. Instead, students will be exposed to the specific processing challenges and associated strategies formanufacturing silicon carbide (SiC) and gallium nitride (GaN) materials and devices, device design
techniques to realize high power performance and high power device electrical characterization. In achieving these objectives, the course aims to offer students with marketable skills that will drive their interest in the wide bandgap device industry, and consequently accelerate their integration into the workforce.

This project is sponsored by NCSU PowerAmerica: Next Generation Electronics Manufacturing Innovation Institute.

Wearable Physiological Monitors for Measuring Canine Stimulus Responses

David L Roberts, Alper Yusuf Bozkurt, & Margaret E. Gruen
07/01/2018 - 09/30/2019

This work will provide a coding system and results of coding behavioral responses of dogs during stimulus testing trials conducted by ORNL staff. The aim is to provide expert interpretation of dogs’ behavioral responses captured on video by ORNL staff during experimental sessions. NCSU will provide a system for coding behaviors pertinent to the behavioral responses identified in video recordings, as well as the result of the application of that system to a corpus of video data provided by ORNL. Design and application of the system will follow existing practices commonly used in scientific studies of veterinary behavior.

This project is sponsored by Oak Ridge National Laboratories - UT-Battelle LLC.

CSR: Small: Middleware Technologies for Multi-Accelerator Clusters

Michela Becchi
06/15/2018 - 05/31/2021

Computing systems are increasingly becoming heterogeneous and leveraging many-core processors and reconfigurable accelerators along with general-purpose CPUs. While GPUs have been part of supercomputers for several years, more recently there has been an increased interest in adding FPGAs to data centers and high-performance computing clusters. A popular example is Microsoft’s Configurable Cloud, a cloud-scale FPGA-accelerated system (consisting of over 5,000 servers) originated from Microsoft’s Project Catapult. Meanwhile, in order to facilitate the adoption of FPGAs, there has been a push towards increasing their programmability through the use of programming models – like OpenCL – intended for multi- and many-core architectures. For example, both Xilinx and Intel are providing their own OpenCL-to-FPGA development toolchain and runtime system. This opens the way for enabling the transparent use of heterogeneous devices on single computers and clusters. These software stacks, however, are meant for the use of FPGAs in a dedicated environment. In addition, given this architectural variety, it becomes difficult for end-users to select the device most suited to their applications.
In this project, we aim to design and develop middleware technologies enabling the transparent and efficient use of diverse accelerator devices on computing systems including FPGAs and GPUs. This research builds of our previous work on the design of scheduling and virtualization techniques for heterogeneous GPU clusters, adding a layer of support for FPGAs and for the efficient combined use of these two accelerator devices. Specifically, this work will target the following issues: first, design of scheduling techniques allowing to map parallel applications on heterogeneous devices, possibly by transparently distributing them across multiple accelerators; second, design of a performance model for predicting the suitability of different compute kernels to different accelerators; third, the design of memory unification techniques to provide a simplified view of the underlying distributed memory system; forth, the study of the opportunity to increase FPGA utilization by space- and time-sharing these devices across applications.

This project is sponsored by National Science Foundation (NSF).

Capacitive Micromachined Ultrasonic Transducer Arrays for Air-Coupled Acoustic Microtapping

Omer Oralkan, Feysel Yalcin Yamaner
06/01/2018 - 12/31/2019

This collaborative work between the research teams of North Carolina State University (NCSU) and University of Washington (UW) aims to build a dynamic elastography imaging system for soft tissue. The imaging system developed by the UW Team has demonstrated the feasibility of a non-contact dynamic elastography imaging of the cornea. The system has mainly two components. An ultrasonic transducer that generates a focused beam to excite the soft tissue (micro-tapping) and an optical coherence tomography unit that captures the mechanical waves generated in the tissue. The work in this project covers the fabrication and system integration of the ultrasonic transducer arrays. The target prototype will have a precise transmit focus control on the surface of the soft tissue and create lateral beam oscillations for shear wave imaging.

This project is sponsored by University of Washington.

Health Analytics Tooling: Retrieval, Assessment Decision and Trending

Hamid Krim
06/01/2018 - 11/30/2019

With a focus on Diabetes in Phase 1, we propose the development of a comprehensive tool which will systematically and seamlessly navigate across the various hybrid data accessible through UNC Medical Records, with a health assessment enabling capability as well as various possible trends. More specifically, we plan on fully exploiting the tools of machine learning and bring them to bear on each step of the data analysis and exploitation. In close consultation with the health specialists, we will develop a mapping mechanism of qualitative data to the quantitative space, thus homogenizing the data. In addition, we plan to design a “Decision Tree” (DT) adapted to our homogenized data. We will exploit the characteristic computational efficiency of tree structures to comb through each patient’s data to yield a quantifiable assessment of interest (e.g. patient is cured as a result of treatment, follow up visits, prescription follow up, and cross validated with State Vital Records). Note that the proposed DT-based analyses not only play a key role in the analysis of trends across populations of patients, but also can also be used to conduct other global statistical analyses (e.g. probabilistically determine a permanent cure conditioned on a life style).
Our plan is to have a Personal Computer-based menu-driven tool with a comprehensive set of options, including visualizations, to carry through a thorough exploration of data; the planned interactive operation will necessitate some attention to identifying and solving all computational bottlenecks in this process.

This project is sponsored by UNC - UNC Chapel Hill.

Highly Robust Integrated Power Electronics Packaging Technology

Douglas C Hopkins, Subhashish Bhattacharya
06/01/2018 - 07/31/2020

NCSU is proposing research in very high voltage (VHV) >10kV power electronics packaging for ultra-harsh environments that use Wide Band Gap (WGB) power semiconductor devices, i.e. SiC (and GaN for gate drivers). The primary problems in VHV circuits are high electric fields that require tailored conductor patterns for field management, minimization of intercoupling capacitances between switching devices, and electrically isolated thermal management. With the fast switching a new concept is pursued using “substrate-less” power module substrates. The power semiconductor interconnections are made through highly thermally conductive organic dielectrics, specifically Epoxy Resin Composite Dielectric (ERCD) material. The ERCD allows for very thin electrically isolating layers to improve electrical conductance, while allowing low modulus material to be used for higher reliability. Lastly, the ERCD material can operate continuously at 300ºC providing early exploration for packaging of WBG devices that are trending to higher temperatures.

This project is sponsored by US Army - Army Research Laboratory.

EAGER: Recomputation-Based Checkpointing for Sparse Matrices

Yan Solihin
05/15/2018 - 04/30/2020

As high-performance computing relies on an increasing number of nodes and components, Mean Time To Failure (MTTF) suffers. Long-running computation is likely interrupted with failures before completing. Checkpointing is a critical technique that allows computation state to be saved so that when a failure occurs, a recent checkpoint can be restored and computation can re-run from the checkpoint rather than restarting from the beginning.

Recently, non-volatile memory technologies have been advancing rapidly, and some of them are a strong contender for use as a future main memory, either for augmenting or replacing DRAM. One such an example is 3D Xpoint memory, which will be brought to market in 2017 by Intel and Micron. These new non-volatile main memory (NVMM) technologies are byte-addressable and have access latencies that are not much slower than DRAM. NVMMs are expected to have a limited write endurance, making it imperative to keep the number of writes low. Despite the limited write endurance and relatively high write latency compared to DRAM, NVMMs’ density and cost advantage over DRAM, and near-zero idle power consumption make them a compelling candidate to replace or augment DRAM in high performance computers.

NVMM provides a new opportunity to rethink how checkpoint/restart is supported because main memory can now hold the persistent state of a program, thereby serving the same role as a checkpoint. Furthermore, NVMM gives programmers direct control over which state is persistent and how that state is used to recover after a failure. It may still be necessary to periodically save a full checkpoint elsewhere in the event of a complete node failure that makes the NVMM inaccessible, but otherwise failures can be recovered by directly re-executing from the persistent state in NVMM.

In contrast, prior approaches to checkpointing rely on taking a snapshot of the application or system state and saving it to secondary non-volatile storage. In {em system-level checkpointing}, the entire memory state of a process is periodically saved to secondary storage. This is a useful and simple programming abstraction for volatile main memory, but it is also inefficient because significant state is copied that is not truly necessary for recovery. System-level checkpointing can lower overheads by using NVM to hold checkpoint state. Since NVM write latency is lower and write bandwidth is higher than hard drive or SSDs, checkpointing overheads can be reduced. However, in this context, NVM is simply a faster secondary storage, not main memory. In {em application-level checkpointing} (ALC), a programmer determines when checkpoints are created and possibly what data structures are included in the checkpoint. A key goal of such prior work was to reduce the amount of memory copied to secondary storage, not to form in-place checkpoints.

We advocate a new approach to reduce the performance and write overhead of checkpointing, and we make the following contributions. First, we observe that a system with NVMM already saves computation in a non-volatile fashion, so we do not need to make additional copies to create a checkpoint. Instead, checkpoints can be constructed {em in-place} in the NVMM utilizing the working data structures used by the applications. Furthermore, we need only persist enough additional state to enable efficient re-execution. Consequently, only very minimal additional state beyond what the program already saves to memory needs to be recorded. Furthermore, our approach is restore-free because no checkpoint needs to be copied back to memory since the required checkpoint is still held in place.

We identify two new approaches for failure-safe in-place checkpointing on NVMM in the context of matrix multiplication: logging and recompute. In the case of logging, we leverage the fact that most of the data is persistent and we log only the data that is currently being modified so that we can reconstruct a consistent state on recovery. In the case of recompute, we do away with the log entirely and allow state to

This project is sponsored by National Science Foundation (NSF).

Hierarchical Control and Information Sharing Methods for Next-Generation Inverter-Interfaced Power Transmission Networks

Aranya Chakrabortty
04/15/2018 - 08/15/2019

This project will develop a distributed hierarchical control architecture for next-generation power transmission networks by using ideas from real-time learning and decision-making. The vision is to consider the future grid with numerous inverter-interfaced generation, FACTS devices, distributed energy resources such as wind, solar, and storage, as well as convention synchronous generators with primary/secondary/tertiary controls, all of which collectively generate thousands of “control points” over wide geographical expanses of the grid. The goal is to design an online hierarchical grid control architecture, starting from the substation with plant controllers, extending to local areas with local-area controllers and going up to a system level for wide-area control and optimal positioning for security constrained real and reactive-voltage setpoint dispatch.

This project is sponsored by Electric Power Research Institute, Inc..

Continuation of Nutrient Effects on Sweetpotato Yield and Shape

Michael D. Boyette, Natalie Genevieve Nelson, & Jonathan R. Schultheis
03/01/2018 - 02/28/2020

The objectives of this research continue and build upon findings of a project begun in 2016 to investigate the influence of different cultural practices, especially different nitrogen types and timing of applications, on the shape and size development and yields of multiple sweetpotatoes varieties.
Additional specific aims are to:
1. Continue to fine tune the unique equipment and analytical methodologies that have been developed in the last two years to scan and analyze the shape and size characteristics of different treatment populations of sweetpotatoes.
2. The ultimate aim of this work is to minimize the production of over/under sized and misshappened sweetpotatoes by identifying those numerous factors that influence size and shape.

This project is sponsored by NC Agricultural Foundation, Inc.

Smart Battery Gauge for Continuous Battery Assessment, CAPER Enhancement Project

Mo-Yuen Chow
03/01/2018 - 03/01/2020

The penetration of energy storage into the grid is low due to the
inability to accurately and constantly assess the State of Charge (SOC) and State of Health (SOH). The Smart Battery Gauge can constantly monitor the batteries to provide live and accurate updates about the battery’s status to alleviate these issues

This project is sponsored by Clemson University.

SiC-Based Wireless Power Transformation for Data Centers & Medium Voltage Applications

Subhashish Bhattacharya
01/31/2018 - 01/31/2020

Eaton, working with NETL and NCSU, will develop high-power density SiC-based wireless power AC-DC converter technologies. Such technologies can convert power from medium voltage to DC output voltage for distribution system applications requiring ease of service, safety, efficiency, and power density.
An isolated wireless power link enables medium voltage distribution directly to the point of use, safely stepping the voltage down to application levels without exposing the application hardware and end user to the dangers of the proximity of medium voltage and hazardous arc-flash. Operating the converter in resonant mode minimizes harmonics, reduces EMI due to the sinusoidal output waveform, and prevents faults on the secondary side from cascading to the medium voltage bus (a fault will cause a loss of resonance and disrupt power flow). This technology will enable simplification of the distribution system by eliminating a transformer and reducing the distribution current level, which will reduce the use of copper, leading to reduced system cost and improved system efficiency

This project is sponsored by Eaton Corporation.

A Therapeutic Cell Distillery: Light-Controlled Fractionation of Stem Cells for Next-Generation Biomanufacturing Processes

Stefano Menegatti, Donald Osvaldo Freytes PhD, & Michael Daniele
01/01/2018 - 12/31/2020

We propose to develop a light-controlled adsorbent to separate (distill) red blood cells into fractions characterized by different densities of surface protein receptors.

This project is sponsored by National Science Foundation (NSF).

Applying Machine Learning to Back End IC Design, Center for Advanced Electronics through Machine Learning (CAEML) Core Project 2A7 funded with industry membership dues.

William R. Davis, Paul D. Franzon
01/01/2018 - 12/31/2019

In this project, we have two major research objectives (1) how to set up a digital integrated circuit synthesis and physical design flow to meet specific goals, and (2) to determine how to achieve this mapping for a variety of designs. We will start by producing surrogate models for a range of designs, both those sourced at NCSU and those obtained by from member companies of the CAEML center. These models will be used to determine that setup automation and trade-off automation can be easily achieved for a specific design. Then we will start evaluating possible classification vectors that can be used to characterize designs.

This project is sponsored by University of Illinois - Urbana-Champaign.

RER-3D: A Research Center for Radiation Effects Reliability Mechanisms Unique to 3D Integration (Radiation Effects in 3D Structures)

Paul D. Franzon
10/11/2017 - 10/10/2022

NCSU will assist Vanderbilt in investigating radiation effects on 3D integrated circuits.

This project is sponsored by Vanderbilt University.

CNS: SHF: Small: Architectural Support for Efficient and Programmable Non-Volatile Main Memory

James Tuck
10/01/2017 - 09/30/2020

Non-Volatile Memory is advancing and may soon replace DRAM and disk as a unified memory and storage device. For instance, Intel and Micron announced that their 3D Xpoint memory will be in the market in 2017. This breaks the conventional view of computer systems with separate memory and storage systems, and requires that future systems be redesigned to support the new possibilities this integrate provides. One problem is that processors will be able to access storage directly using loads and stores, and current processors do not guarantee that stores update memory in the order specified by the programmer. This means that updates to memory and storage may happen out of order resulting in an inconsistent state during a system failure or power-loss. Dealing with failure-safety adds new complexity to software and additional performance overheads on these future systems.

This project will investigate new techniques that help programmers write high performing and efficient code for future systems that use non-volatile main memory. In particular, techniques that simplify programming while accelerating performance are sought. A promising direction for solving some of these problems is speculative execution. Speculation has been successfully used to make parallel programming easier and to speed up execution in the presence of long latency memory accesses. Many of the problems raised by non-volatile memory are similar to the ones that speculation has been applied to in the past. This proposal takes a systematic look at how speculative execution can make future NVM systems more efficient and more programmable.

This project is sponsored by National Science Foundation (NSF).

High Temperature Embedded/integrated Sensors (HITEIS) For Remote Monitoring Of Reactor And Fuel (previous title High Temperature Embedded/integrated Sensors (hiteis) For Remote Monitoring Of Reactor And Fuel Cycle Systems)

Xiaoning Jiang, Mohamed A. Bourham, & Mo-Yuen Chow
10/01/2017 - 09/30/2020

In this project, we will develop high temperature (> 600 C) embedded/integrated sensors (HiTEIS) for wireless monitoring of reactor and fuel cycle systems. HT pressure sensors, vibration sensors and liquid level sensors will be designed, fabricated, embedded and characterized, followed by nuclear structure integration and evaluations. The proposed technique will likely be used to enhance the safety and efficiency of nuclear power systems.

This project is sponsored by US Dept. of Energy (DOE).

2.5D Extendible Processor

Paul D. Franzon, James Tuck
09/30/2017 - 09/30/2021

Hardware extendible processor.

This project is sponsored by US Navy-Office Of Naval Research.

Trusted Fabrication through 3D Integration Demonstration

Paul D. Franzon
09/30/2017 - 12/31/2019

NCSU and Draper will investigate the design and fabrication of trusted 3D electronics.

This project is sponsored by US Navy-Office Of Naval Research.

Doping of Diamond and c-BN beyond Thermodynamic Solubility Limit for Solid State Devices

Jagdish Narayan, Ki Wook Kim
09/28/2017 - 09/27/2020

This research program proposes a transformative approach to n- and p-doping of diamond and c-BN beyond the current state-of-the-art. The main concept is based on the recently discovered direct conversion of amorphous carbon into diamond and h-BN into c-BN at ambient temperatures and pressures in air in the form of large-area single-crystal films on substrates such as sapphire and silicon. The key advantage stems from the novel growth method, where the carbon layers are melted by using high-power nanosecond pulsed lasers in a highly super undercooled state, and then quenched rapidly either into a new state of carbon or into the single-crystal diamond phase in the presence of a template for diamond growth. Similarly, h-BN can be melted in a super undercooled state and converted into large-area single-crystal c-BN films. Accordingly, it is envisioned that dopant impurities present in the amorphous carbon and h-BN films can be incorporated into substitutional sites of diamond and c-BN during rapid liquid-phase crystallization via the phenomenon of solute trapping. As the proposed approach is a fundamentally nonequilibrium process, dopant concentrations in electrically active sites for both n- and p-types can far exceed the thermodynamic equilibrium solubility limits, while maintaining the energy levels, overcoming the long-standing challenge of diamond.

Specifically, the feasibility studies on n-type doping (N, P, As and Sb dopants) will be carried out by incorporating these dopants into carbon by ion implantation, followed by rapid recrystallization from super undercooled state into epitaxial diamond thin film heterostructures. Similarly, n-type and p-type doping of c-BN will be achieved by Si and Zn dopants, respectively. The p-type (B dopants) doping of diamond will be accomplished by pulsed laser deposition of boron doped carbon layers at 500C in the presence of oxygen and hydrogen. Our preliminary results on nitrogen doping in diamond have already indicated that the dopant concentrations in electrically active substitutional sites can indeed be much beyond the thermodynamic solubility limits. Lattice location (substitutional versus interstitial) studies will be performed by using atomic resolution techniques and the results correlated with electrical activation and detailed carrier transport measurements. Theoretical calculations of dopant energy levels, ionization efficiencies, carrier concentrations and mobilities will be carried out in parallel to establish correlations with experimental results and to guide the fabrication of novel solid state devices. A primary goal of the combined effort is to demonstrate the p-n diodes of diamond and c-BN with satisfactory junction characteristics by controlling the dopant concentrations and the types vertically and/or laterally in the process. When successfully implemented, the proposed research is expected to revolutionize the doping and practical applications of diamond as well as the related materials such as c-BN.

This project is sponsored by US Army - Army Research Office.

Modeling of Vibration-Enhanced Underground Sensing (VENUS)

Michael B. Steer, Mohammed A. Zikry
09/08/2017 - 09/07/2019

Humanitarian demining will be advanced by exploiting a new sensing modality based on magnetically induced vibrations of small metallic parts. An alternating or pulsed magnetic field induces vibrations of structures containing diamagnetic and paramagnetic materials. If these materials are conductive then the primary mechanism driving vibrations is the induction of eddy currents and subsequent Lorentz forces. While the physics is known, the analytic modeling is intractable which affects the ability to optimize a vibration-enhanced underground sensing system (VENUS). The main problem addressed in this proposal is researching a working mathematical model of a complex interacting system involving multiple physics, multiple scales, and multiple analysis domains. This project will explore the abstraction levels necessary to achieve usable multi-physics simulations of magnetically induced mechanical vibrations accounting for different material types, ageing effects, construction variability, and the effect of different soil types.

This project is sponsored by Vadum Inc..

A Whole-Brain Ultrasonic Neural Stimulation And Photoacoustic Recording System In Behaving Animals

Omer Oralkan
09/01/2017 - 08/31/2019

This project aims to develop a 2D capacitive micromachined ultrasonic transducer (CMUT) array with integrated electronics and optics that is capable of ultrasonic neural stimulation in 3D volume by dynamic transmit beamforming and real-time recording of hemodynamic activity in response to stimulation by volumetric photoacoustic imaging. The described technology will equip the neuroscience community with a research tool to further explore the emerging field of ultrasonic neural stimulation and to monitor metabolic/hemodynamic responses in awake/behaving animals with real-time photoacoustic imaging.

This project is sponsored by National Institutes of Health (NIH).

EAGER: Collaborative Research: Spatially Continuous Modeling of Power System Oscillations with Renewable Energy Penetration

Aranya Chakrabortty
09/01/2017 - 08/31/2020

In a large power network, where widely dispersed generators are interconnected through tielines, the essential characteristic that provides flawless power transmission through the network is synchronized swing of all generators. However in the presence of any disturbances, which may be caused due to any number of reasons including generation trips and outages or load changes, asynchronous motion can result. Such a motion leads to oscillations in the rotation frequency and angle as it can lead to increasing frequency swings, which are denoted as swing dynamics. This problem has been addressed extensively and is the subject of numerous publications. Most of the existing approaches are based on spatially discrete modeling, implemented by ordinary differential equations (ODEs), and focus on analysis and synthesis using the ODE-models. Our thesis, in contrast, is that when the number of generators is relatively large the fundamental mechanism that produces the phase and frequency oscillations is a continuous one. As a result, accurate and physically oriented methods for mitigating and suppressing these oscillations are better realized through the use of partial differential equations (PDEs). We therefore propose a PDE-based approach for modeling the power grid.

This project is sponsored by National Science Foundation (NSF).

Making of and Prototype Development for the ASSIST HET Testbed

Alper Yusuf Bozkurt
09/01/2017 - 08/31/2019

In this project, we focus on the prototype development for various generations of Health and Environmental Tracker (HET) Engineered System. The “making” of the HET engineered system hardware in this project complements the efforts for its deployment in clinical experiments (a different project proposal submitted by CSE Mr. Strohmaier). This project also provides technical support to integrate Thrust 3 research products (various low power ASSIST sensors) into the HET wearables (wristband and chestpatch). The major focus of this project in Year 7 is to populate sufficient number of HET 1.0 and 2.0 devices/prototypes for clinical data collection and facilitate the processing of the HET Testbed data.

This project is sponsored by NCSU Advanced Self Powered Systems of Sensors and Technologies (ASSIST) Center.

Natural Variation and Systems-Level Properties of Gene Regulation in Drosophila

Gregory T Reeves, Cranos Williams
09/01/2017 - 05/31/2022

Progress Report

This project is sponsored by National Institutes of Health (NIH).

Development Of Remote Sensing Tools And Associated Analysis Methods For Crop Phenotypic Traits

Michael Kudenov, Ronnie W. Heiniger
08/15/2017 - 12/31/2019

The proposed work for this project focuses on the development of machine learning training procedures and image post-processing and acquisition procedures. These methods will be applied to quantifying traits in agricultural applications and breeding.

This project is sponsored by Syngenta Crop Protection, LLC.

A Novel Three-Dimensional Thin-film Thermoelectric Generator for Wearable Applications

Daryoosh Vashaee, Mehmet C. Ozturk
08/01/2017 - 07/31/2020

An integrated research, education, and outreach program is proposed that will introduce a novel, highly efficient, photo-enhanced thermoelectric generator. The new device, which has the potential to transform the thermoelectric industry will provide > 100X improvement in output voltage compared to conventional devices. The new device achieves this performance enhancement thanks to an entirely new device architecture, which significantly reduces the parasitic losses as well as its ability to harvest both photoexcited (light) and thermoelectric (heat) carriers. The program has four main goals:
1. Device Demonstration: A CMOS compatible, wafer-scale micro-fabrication process will be developed to fabricate a highly efficient, photo-enhanced thermoelectric energy generator (PTEG) on inexpensive silicon wafers. The fabrication will rely on mature processes and techniques used in micro-electro-mechanical-systems (MEMS) integration.
2. Material Development: The work will focus on improving the material properties for room-temperature applications. A particular composition of Si(1-x)Ge(x) providing high degeneracy of the band minima (N=10) is proposed. Nanostructuring and partial amorphization of the semiconductor material will be used to further improve the figure-of-merit ZT using a novel microwave method previously introduced by the principal investigator.
3. Modeling: A comprehensive system model will be developed to optimize the device architecture. The effort will include both thermal and semiconductor modeling, which will focus on carrier transport, photoexcitation, and ambipolar diffusion.
4. A broad education plan will be developed including a new teaching initiative in the upper-division undergraduate curriculum, involvement of undergraduates in research, and outreach, with aims to introduce energy conversion materials to the general public.
Intellectual merit:
The proposed photo-enhanced thermoelectric generator has the potential to revolutionize the way the thermoelectric modules are manufactured. While this proposal focuses on energy harvesting, innovations introduced to the device architecture are also applicable to thermoelectric devices intended for cooling or infrared imaging applications. The specific material and device configuration used in this proposal has a broad range of indoor applications ranging from wearable electronics for monitoring of human health and environmental conditions to commercial systems that require self-powered, continuous and wireless monitoring. The proposed device architecture is compatible with modern thin film thermoelectric materials and manufacturing processes.
We anticipate that this research should lead to (a) discovery of new ways to harvest both light and heat energy, and (b) a competitive silicon-compatible thermoelectric material for room temperature applications. The device is particularly efficient for use with complex systems that involve sensors and electronics. Hence, it will potentially have high commercial market acceptance in emerging, self-powered, connected sensor systems. This program is a natural extension of a highly fertile line of leading research by the PIs, which has generated many publications in top ranked journals, and has been featured in both wide and specialized audience journals (Science, Nature, PRL, etc.).

This project is sponsored by National Science Foundation (NSF).

Energy Management Strategies for Hybrids and Microgrids

Ning Lu, Srdjan Miodrag Lukic, & David Lee Lubkeman
08/01/2017 - 12/31/2019

There are three main objectives of the NCSU 2019 project:
1. OPAL-RT HIL system technologies transfer to Total Lyon (Q1-Q2)
2. Faster than real time simulation in OPAL-RT/HIL (Q2-Q4)
3. MW-level microgrids modeling and simulation in the HIL system towards solar farm/refinery and/or island cases (Q2-Q4).

The completion of the technology transfer will enable the Total team to use the OPAL-RT HIL testing facilities at the NCSU GridWrx lab and replicate a similar OPAL-RT HIL test system at the Total Lyon test site. Technical extensions of the existing HIL testbed in faster-than-real-time simulation and MW-scale microgrid will allow cost benefit study to be conducted on the HIL testbed for both commercial and MW-scale microgrids considering the operation dynamics and coordination among different control systems.

This project is sponsored by TOTAL Solar International.

Retrofit Control: A New, Modular Gyrator Control Approach for Integrating Large-Scale Renewable Power

Aranya Chakrabortty
08/01/2017 - 07/31/2020

This project will address the growing concerns of wind and solar power integration from the perspective of power system dynamics and stability. We propose a new retrofit control technique where an additional controller is designed at the doubly-fed induction generator site inside the wind power plant, or the power electronic converter models for battery satorage units that may be accompaying a wind or solar power plant. This controller cancels the adverse impacts of the power flow from the wind side to the grid side on the dynamics of
the overall system. The main advantage of this controller is that it can be implemented by feeding back only the wind states and wind bus voltage without depending on any of the other synchronous machines in the rest of the system. Through simulations carried out in our hardware in the loop testbed at the FREEDM center we plan to show how the proposed control technique can efficiently enhance the damping performance of a power system variable despite very high values of renewable penetration.

This project is sponsored by National Science Foundation (NSF).

SaTC: CORE: Small: Towards Smart and Secure Non Volatile Memory

Huiyang Zhou
08/01/2017 - 07/31/2020

This research investigates smart and secure technologies for non-volatile memory.

This project is sponsored by National Science Foundation (NSF).

Robotics Awake: Promoting the Diffusion of Innovation through Curriculum Development and a Technician Training Community College Extension Model

Edgar J Lobaton
07/01/2017 - 06/30/2020

Wake Technical Community College (Wake Tech) will collaborate with industry partners and NCSU to develop curriculum for training technicians in the operation, utilization, and programming of light industrial robots in advanced manufacturing while developing a model for using technician training as a basis for community college extension work to promote the diffusion of innovations likely to contribute to regional economic development. The main activities include; creation of an industry partnership group focused on integration of co-robots in local manufacturing plants, professional development for faculty from Wake Tech and three neighboring community colleges, industry extension, development and implementation of two courses and certificates (Collaborative Robotics Technician and Robotics Programmer Technician), equipment purchases to support hands-on curricula, recruiting students, and a case study to develop a model for future community college extension work in the diffusion of innovation through technician education.

This project is sponsored by Wake Technical Community College.

University Leadership Initiative; Hyper-Spectral Communications, Networking & ATM as Foundation for Safe and Efficient Future Flight: Transcending Aviation Operational Limitations with Diverse and Secure Multi-Band, Multi-Mode, and mmWave Wireless Li

Ismail Guvenc
06/12/2017 - 09/29/2020

This research will address the Aeronautics Research Mission Directorate’s (ARMD’s) Strategic Thrust (ST) #1, Safe, Efficient Growth in Global Operations. The research outcomes fit within the ARMD’s Strategic Implementation Plan (SIP) years 2025-2035 and beyond 2035 time frames, and will contribute specifically to the following outcomes: (i) fully integrated terminal, enroute, surface and arrivals/departures operations (ATM+2), and (ii) fully autonomous trajectory services (ATM+3).

As is well known, air travel and air transport are expanding rapidly. Unmanned aircraft system (UAS) use is burgeoning. An obvious consequence of the growth in passenger and freight air traffic, and the coming of UAS into the worldwide airspace, is continuing growth in air traffic density and complexity. Although initially UAS will fly in airspace separate from piloted aircraft, there will inevitably come “mixed airspaces,” and likely full integration of UAS throughout the complete current worldwide airspace (and in the future, beyond, e.g., stratospheric flights). The addition of UAS will compound the already increasing complexity of air traffic management (ATM). The increase in density (aircraft per unit volume) means that safe operation will become more challenging. The situation is more complex for ATM than for terrestrial commercial communications, because of greater aircraft mobility and much more stringent reliability requirements. Since safe operation cannot take place without highly-reliable and efficient communications and networking among aircraft, ground stations, and other entities, we are proposing research to dramatically enhance the capabilities of aviation communication and networking systems. Hence, the research areas of our investigation are aeronautical communications, networking, and ATM, including aspects of navigation and surveillance, for both manned and unmanned aircraft.

This project is sponsored by University of South Carolina.

Eager: Tandem Solar Cells of Two Dissimilar Material Systems

Salah M. Bedair
05/01/2017 - 04/30/2020

We propose two years research program to address the current issues of connecting two solar cells in a tandem structure. The propose approach is versatile and can be applied to several solar cell combination’s with different band gaps. It also lifts the current restrictions of lattice matching for the tandem cell components and can also be used to connect cells made of materials with different expansion coefficient.

This project is sponsored by National Science Foundation (NSF).

RESEARCH AREA 4: ELECTRONICS: Reconfigurable Electrofluidic Networks for Highly Adaptive Electronic Warfare Platforms

Jacob James Adams
04/21/2017 - 04/20/2020

Military communication, navigation, and radar systems must operate in electromagnetically contested environments with high fidelity. In this environment, the ideal electromagnetic (EM) platform consists of a multi-functional (sensing, communications, electronic attack) and highly adaptive, able to generate and sense radiation across a wide range of frequencies, with controllable directional and polarization sensitivity. Among the critical needs for such “smart” radios are reconfigurable antennas that can dynamically change their radiation patterns or frequency response. Here we propose networks of liquid metal embedded in the skin of a vehicle, aircraft, or other communications/sensing platform. These electrofluidic (EF) networks are physically reconfigurable – the conductors can be moved in and out of particular channels to change the electromagnetic characteristics of the platform. The proposed work encompasses several goals towards controlling and realizing these EF networks.

This project is sponsored by US Army.

Amorphous and Nanocomposite Magnets for High Efficiency, High Speed Motor Designs

Subhashish Bhattacharya
03/01/2017 - 09/30/2020

Amorphous and Nanocomposite Magnets for High Efficiency, High Speed Motor Designs
Electric motors use soft and/or hard ferromagnets to produce or direct spatiotemporally varying magnetic flux. World Bank reports [1] the US consumed ~4 trillion kW-h of electricity in 2009 with ~30% consumed by motors. New materials can reduce losses (~58%) between the rotor and stator with a 1% improved motor efficiency results in saving ~12 billion kW-h. Rare earth (RE) permanent magnet (PM) motors are popular but soft magnetic materials (SMMs) provide the greatest potential for energy savings [2-4]. Supply constraints on RE elements (China controls ~ 80%), cause concerns which led NATO to classify them as critical elements [5-6]. We will demonstrate RE-free 5 kW motors with 4% increased efficiency using metal amorphous nanocomposite (MANC) SMMs. A 200 W power loss, portioned equally, will need power reductions of: a) controller: 50 W; (b) copper loss: 50 W; (c) iron loss: 50 W; (d) windage, 50 W.
MANCs are a transformational technology to increase efficiency and limit RE use in high speed electric motors (HSEMs). Hybrid motors employ a REPM rotor and high induction SMM stator. New SMMs replacing laminated FeSi in stators can reduce motor size [3-4]. CMU MANC SMMs [7] have inductions comparable to Si-steels and resistivities [8] to enable high switching f’s necessary for high torques to allow motor size and weight reduction. We will investigate MANC motors targeting 1-10 kHz frequencies in stator geometries for HSEMs. Materials development builds on Fe-Co [9], Co-rich [10] and Ni-rich [11] MANCs with high inductions, low losses, strain induced anisotropy and excellent mechanical and high-T magnetic properties. MANC SMMs investigated in high-f ARPA-E power transformation applications resulted in a T2M plan to penetrate motor markets. MANCs have (1) low direct-current (dc) hysteresis losses; (2) thinner laminations offering lower ac eddy-current losses. Lower iron losses than Si steel sheets, allow MANC motors to operate at higher rotational speeds. PPMT (Parallel Path Magnetic Technology) topology motors with Co-base MANCs, as compared to Si steel, allowed a high-speed design reducing machine size (~70 %), and RE hard magnet volume (~83 %).

This project is sponsored by Carnegie Mellon University.

Reu Site:from The Body To The Grid: Joint Erc Reu Explores Energy From Nano-scale Harvesting To Smart Grid Technology

Iqbal Husain, Elena N Veety, & Pam Page Carpenter
03/01/2017 - 02/29/2020

The project described here is a supplement request to augment the REU Site: From the body to the grid: Joint ERC REU explores energy from nano-scale harvesting to smart grid technology. The supplement is for 2 RET participants to augment the REU site proposal.

This project is sponsored by National Science Foundation (NSF).

SHF: Small: Collaborative Research: The Automata Programming Paradigm for Genomic Analysis

Michela Becchi, Gavin Conant
03/01/2017 - 07/31/2019

Thanks to recent advances in DNA sequencing technology, a number of genomic analysis tasks – such as reference-based and de novo sequence assembly, taxa identifications in metagenomic sequences, orthology inference and regulatory motif search – can nowadays operate on increasingly large volumes of data. All these applications perform, at their core, some kind of pattern matching operations, a computation that maps naturally onto finite automata abstractions. It has been shown that large scale automata processing can be efficiently accelerated on streaming architectures such as Field Programmable Gate Arrays (FPGA). However, the low level programming interface of these devices has hampered their widespread adoption within the bioinformatics community. As an alternative, Micron Technology has recently announced its SDRAM-based Automata Processor (AP), which will come with an automata-based programming interface. However, the position that this emerging technology will take in the realm of existing streaming accelerators is unclear: in particular, its capabilities in handling big data and diverse computations as well as its programmability must still be understood. In this research we aim to study novel programmatic descriptions of several genomic analysis tasks obtained by re-describing each operation using an automata-based programming model, and map such this programming model onto FPGA platforms and onto Micron’s AP. Our goal is two-fold: on one hand, we aim to facilitate the adoption of these accelerators within the scientific community; on the other, we seek to investigate the benefits and limitations of these technologies when targeting a variety of pattern matching operations at large scale.

This project is sponsored by National Science Foundation (NSF).

Understanding and Accelerating Information Spreading in Dynamic Networks. ARO Research Area 10: Network Science – 10.1 Communication and Human Networks

Huaiyu Dai
01/31/2017 - 01/30/2020

In many existing and emerging large-scale networks, an important application is to spread the information quickly and efficiently over the network. Over the past decade, this topic has received great research interest, and is relatively well studied for static networks. In contrast, our knowledge is far from complete when the network structures change over time, which is typical due to various reasons including environment changes, device and user mobility, variation of social relationship, and growth of the networks. There have been extensive studies on protocol and algorithm development in the area of mobile wireless networks, but many of them resort to simulation and
experimentation with synthetic and real-world mobility traces; a general analytical framework is lacking. In this project, built on our promising preliminary results, we intend to work towards a unified analytical framework for mobile networks that can address various types of mobility patterns and handle both connected and delay-tolerant networks. We also plan to extend our study to mobile social networks, which possess some unique features for information spreading that deserve separate and in-depth considerations. As emerging networks are complex and exhibiting unpredictable dynamics, random-walk based
algorithms become an appealing architectural solution for them. A pertinent question is whether we can further improve the efficiency of these algorithms while maintain their simplicity and robustness. Our preliminary results indicate that, by exploiting some additional information which may readily be available, a speedup by an order of magnitude is potentially achievable. Underlying our efficient algorithms is a design framework based on non-reversible Markov chains. In the second research thrust, we plan to deepen our study on this design framework, and further extend its underlying principle to the study in mobile social networks. The proposed research will be assessed through a comprehensive evaluation plan.

This project is sponsored by US Army - Army Research Office.

HV SiC MOSFET Enabled Solid State Transformers (SST) for MUSE (Mobile Utility Support Equipment) based Nano-Grid Applications

Subhashish Bhattacharya
01/03/2017 - 09/30/2019

Functionalities will be added for online monitoring of the Power devices including:
• Online monitoring of VDS for device health assessment. This will be done by modifying the existing gate driver circuitry.
• Online estimation of the device junction temperature by measuring the base plate temperatures and feeding the data to a detailed thermal model of the designed converter.
• Active modulation of the gate resistance during the switching transients to control the voltage and current overshoots of the power devices. The static characterization of the XHV-6 modules will be done to figure out the variability among the different modules. Furthermore, several protection features will be added including AC and DC short circuit protection, AC and DC over voltage and over current protection. We will attempt to create a user interface to be implemented for the end users which will show real time date of the MUSE SST system.

This project is sponsored by US Navy - Space and Naval Warfare Systems Center (SPAWAR).

Behavioral Modeling for High Speed Links, Center for Advanced Electronics through Machine Learning (CAEML) Core Project 1A5 funded with industry membership dues.

Paul D. Franzon
01/01/2017 - 08/15/2019

Modeling High Speed Links as part of the CAEML IUCRC.

This project is sponsored by University of Illinois - Urbana-Champaign.

CAREER: Compiler and Runtime Support for Irregular Applications on Many-Core Processors

Michela Becchi
01/01/2017 - 01/31/2020

The overall goal of the project is the design of compiler and runtime techniques to effectively deploy graph and other irregular applications on many-core processors, while hiding from the programmer the complexity and heterogeneity of the underlying hardware and software stack. Since the degree of parallelism within irregular applications is heavily data dependent, the proposed compiler techniques will aim to generate multiple platform-specific code variants starting from high-level platform agnostic algorithmic descriptions. The runtime techniques will focus on the selection of the most appropriate code variant and its tuning to the underlying hardware and the input datasets.

This project is sponsored by National Science Foundation (NSF).

Intellectual Property Reuse through Machine Learning, Center for Advanced Electronics through Machine Learning (CAEML) Core Project 1A2 funded with industry membership dues.

Brian Allan Floyd, Paul D. Franzon
01/01/2017 - 08/15/2020

In this project, machine-learning techniques will be investigated and applied to the problem of facilitating design optimization and intellectual property re-use.

This project is sponsored by University of Illinois - Urbana-Champaign.

SHF: Medium: Collaborative Research: A Comprehensive Methodology to Pursue Reproducible Accuracy in Ensemble Scientific Simulations on Multi- and Many-Core Platforms

Michela Becchi
01/01/2017 - 05/31/2020

The overarching goal of this project is to tackle reproducibility problems due to the use of floating point arithmetic in scientific simulations running on parallel platforms that include multicore processors coupled with many-core accelerators. Specifically, the project encompasses two major goals/activities:
First, identify common sources of accuracy errors and study their accumulation, propagation, and runtime effects in a controlled environment. This phase includes three research activities: (i) modeling into code motifs those computations that may lead to accuracy errors; (ii) providing multiple implementations of these motifs, which we call code inspectors, targeting different parallel platforms; and (iii) evaluating the accuracy and runtime of these implementations using a variety of datasets and stress conditions.
Second, install these code inspectors in real scientific code bases and, thus, study their behavior in uncertain environments. This phase includes two research activities: (i) prioritizing code segments based on quantitative impact scores and matching segments to inspector motifs and (ii) finding the optimal code inspector implementations and patching the code with them so as to optimize the overall result variance.

This project is sponsored by National Science Foundation (NSF).

NeTS: Small: Collaborative Research: Towards Millimeter Wave Communications for Unmanned Aerial Vehicles

Ismail Guvenc
10/01/2016 - 09/30/2019

With the proliferation of bandwidth hungry mobile devices, dense deployments of users, and the proliferation of Internet of Things (IoT) technologies, broadband spectrum needs have been continuously increasing in recent years. The use of the millimeter wave (mmWave) frequency bands is seen as a major way to address this spectrum crunch problem since large amounts of licensed and unlicensed bandwidths are available at these frequencies, leading to new standards being developed for 5G cellular and Wi-Fi using mmWave. In parallel, there have been unprecedented recent advances in commercial unmanned aerial vehicle (UAV) technologies, which has resulted in their adoption in a wide range of applications, such as disaster relief, agricultural monitoring, wireless connectivity in rural areas, and hotspot connectivity for major sporting events.

The proposed research in this project aims to study the foundations of mmWave communications in UAVs in a systematic manner using notions from wireless networks, communication theory, optimization theory, and software defined radios (SDRs), starting from channel sounding and characterization. A key challenge in any mmWave communication is that beamforming needs to be used in order to overcome the path loss. The use of mmWave on UAVs poses additional challenges and benefits. The challenges are primarily due to limited battery life and weight carrying capability of UAVs and the benefits accrue from the use of: 1) large bandwidth; 2) ability to implement 3D beamforming enabling improved spatial reuse; and 3) harnessing the UAV mobility to perform dynamic UAV clustering and interference management. The goal of this project is to address these fundamental challenges via a unique research collaboration focused on developing the next-generation of analytical and experimental tools for designing, modeling, optimizing, and testing mmWave UAV networks. Specific areas of study will include: (i) novel precoder designs for mmWave UAVs taking into account realistic propagation characteristics derived from channel sounding experiments; (ii) equalizer design for mmWave UAVs that trade-off beamwidth against equalizer structure; (iii) multiple access design for mmWave UAVs: code division and time division multiple access techniques will be revisited for mmWave UAV communications, for serving users that are accessed by the same transmitter beam; and (iv) optimal UAV placement for multi-hop wireless backhaul: investigating the use of UAVs as flying relays.

This project is sponsored by Florida International University.

Modeling and Characterization of Wideband Communications Via Narrowband Channels Using Direct Modulation

Jacob James Adams
09/15/2016 - 09/14/2019

Long distance communications rely on HF, VHF, and UHF wireless systems where wavelengths are over 1 meter long. Conventionally, resonant antennas are used in mobile applications in these bands, due to the large size required for more broadband structures. A resonant antenna in steady state can only effectively transmit a narrow range of frequencies. However, if the antenna’s properties are modulated at a rate on the order of the symbol frequency, then the antenna becomes a time variant system that may circumvent the physical limitations of small antennas. Experiments have indicated that unusually wideband emissions from small antennas are possible, though further study is needed to address the fundamental questions in this area and improve the present understanding of time-varying radiators. The overall scientific goal of this proposal is to establish models and design methodologies for radiating systems with rapidly time-varying properties.

This project is sponsored by Defense Advanced Research Projects Agency (DARPA).

Snapshot Imaging laser Displacement Sensor for Hypervelocity Diagnostic Testing

Michael Kudenov
09/14/2016 - 09/10/2019

Reentry and hypersonic low- and mid-altitude vehicles are subjected to significant aerothermal heating as kinetic energy is dissipated into the atmosphere. Designing a vehicle to withstand aerothermal heating and other associated aerodynamic loads poses a significant engineering challenge in materials research. In the development of materials- and physics-based models, significant testing is conducted in hypersonic wind tunnels. Deformations in a surface or material can be related to internal stresses; thus, measuring such deformations, in situ, within the hypersonic environment must be achieved without distrubing the hypersonic characteristics of the flow. This project will develop high speed optical metrology equipment, optimized for use in hypersonic wind tunnel testing.

This project is sponsored by Control Vision, Inc..

Wearable Patch Reader for Peripheral Artery Disease

Michael Daniele, Alper Yusuf Bozkurt
09/03/2016 - 06/30/2020

Current treatment of peripheral artery disease (PAD) rely heavily on the angiographic appearance of the arteries following re-vacularization without information on tissue oxygen levels. Ensuring tissue oxygen levels are adequately restored during treatment and continually monitored post-procedure is highly desirable. There is currently no reliable methodology by which physicians can ascertain if there is adequate tissue oxygen to heal an ulcer and ensure tissue oxygen levels persist post-procedure. To remedy this practice gap, Profusa’s continuous, injectable micro-oxygen sensing hydrogel provides a low-cost, real-time, mobile, peripheral tissue oxygen measurement before, during and after revascularization therapies. We propose the use our O2 sensors before, during, and after vascular interventions to improve therapeutic decision-making and outcomes. However, there is an imminent need for a wearable optical reader for continuous monitoring to make a significant impact and transform the way healthcare is provided for PAD patients`. The goals of this Phase II SBIR are: 1) to convert Profusa’s bulky optical reader into a flexible format that conforms to the foot, and 2) to demonstrate skin biocompatibility of the flexible reader patch per ISO 10993 standards as well as clinically validate the flexible reader in comparison to Profusa’s current reader system (i.e characterized sensor response to acute and chronic blood flow changes in the extremities).

This project is sponsored by Profusa, Inc..

CAREER: Towards Broadband and UAV-Assisted Heterogeneous Networks for Public Safety Communications

Ismail Guvenc
09/01/2016 - 03/31/2020

The demand for wireless data communications is increasing far faster than advances in wireless communications, and at the current pace, demand will outpace the available capacity in major markets in just a few short years. To encourage innovation in the area of collaborative spectrum sharing, DARPA organized a Spectrum Collaboration Challenge (SC2) with the stated goal to develop “autonomous collaboration techniques for efficient spectrum sharing,” which aim to yield 100-1000 fold improvements in spectrum efficiency. This supplement is in support of the participation of the NCSU team (team Wolfpack) in DARPA’s SC2 challenge.

The main objective of the proposed supplement is to research, develop, and implement technical solution concepts for collaborative spectrum sharing and to test their performance in head-to-head scrimmages with other competing approaches. In particular, we will research, develop, and test spectrum sharing algorithms that build on fundamental concepts in communication theory, cognitive radios, machine learning, routing, among other technical domains. The proposed methods will also be validated in the DARPA SC2 challenge by competing against other teams, which will allow us to revise and improve our framework as needed.

Wireless communications are affecting deeply the daily lives of the overwhelming majority of people on this planet. The insatiable demand for network capacity has motivated an entirely different approach on spectrum utilization. Work in this proposal will enable new collaboration approaches that will impact the lives of anybody relying directly or indirectly on wireless communications. In addition to direct impacts, national security and public services rely heavily on wireless communications, and thus can indirectly impact the well being of all citizens.

This project is sponsored by National Science Foundation (NSF).

Distributed Energy Storage Device (DESD)

Wensong Yu, Srdjan Miodrag Lukic, & Alex Q. Huang
09/01/2016 - 08/31/2019

The overall objective of this project is to develop a bidirectional, fully functional, efficient and reliable medium-voltage SST. The prototype will directly connect to 7.2kV FREEDM transformer and provide both 380 DC and 240 AC buses.

This project is sponsored by NCSU Future Renewable Electric Energy Delivery and Management Systems Center (FREEDM).

EAGER: Exploring Extreme-Scale DNA-based Storage Systems

James Tuck, Albert J. Keung
09/01/2016 - 08/31/2019

The world’s digital data is growing rapidly and is projected to exceed 16 zettabytes (1021) in 2017. This vast amount of digital data greatly exceeds our ability to store it even when accounting for expected advances in the storage industry. We need extraordinary advances in how we store information in order to catch up.

DNA offers a potentially transformative solution due to its high raw capacity of 1 zettabyte/cm3 (1 exabyte/mm3). To put that in perspective, the best technology available today would require 100,000 cubic meters of volume(10 GB/mm3) to store the equivalent amount of information, more than 10 to the 11th power times less dense. If successful as a storage medium, DNA could hold the world’s entire digital data in a relatively small volume. Also, DNA offers unprecedented reliability. It has a very long life even in relatively harsh conditions compared to electronic media, retaining its structure for hundreds to thousands of years at room temperature.

The overall concept of DNA storage is that extreme amounts of infrequently-accessed information will be stored in DNA, and when needed, subsets of the DNA will be copied to an electronic computer system with more limited but rapid-access storage capacity.

However, DNA is a unique material with very different chemical and physical properties compared to traditional electronic storage media. Thus, the more pertinent question for computer systems experts is determining how to design a high capacity and reliable storage system using DNA given its chemo-physical properties and constraints. This project will investigate some key limitations and design choices for DNA storage systems.

This project is sponsored by National Science Foundation (NSF).

SCH:INT: Novel Textile based Sensors for Inner Prosthetic Socket Environment Monitoring

Alper Yusuf Bozkurt, He Huang, & Tushar K. Ghosh
09/01/2016 - 08/31/2020

This proposal aims at solving a long-standing problem in the field of prosthetics –lack of inner-socket sensor technology. Due to this limitation, monitoring the inner socket environment (such as socket pressure, moisture, and temperature) is impossible. The proposed textile based multimodal sensor interface will be evaluated in real-time inner socket environment monitoring to enable self-management.

This project is sponsored by National Science Foundation (NSF).

Collaborative Research: Modeling The Regulatory Network Of Inositol Phosphate Signaling In Plants.

Imara Y. Perera, Cranos Williams, & Joel J. Ducoste
08/15/2016 - 12/31/2019

Myo-inositol phosphates (InsPs) are signaling molecules that are critically important in a number of developmental, metabolic and signaling processes in eukaryotes. The fully phosphorylated form, inositol hexakisphosphate or InsP6, plays important roles in many eukaryotes. A new frontier for InsP signaling is the study of unique signaling roles for a novel group of InsPs containing diphospho- or triphospho- moieties (PPx) at one or more positions on the Ins ring. In some ways, these PPx-InsPs are analogous to ATP in that they contain high-energy pyrophosphate bonds, and in addition, have been linked to communicating the energy status of the cell in other organisms. In this collaborative project, we previously developed analytical methods to detect and quantify PPx-InsPs in plant tissues, identified and cloned genes encoding the VIP kinases that are responsible for inositol pyrophosphate production in plants, and developed genetic resources to examine function of the Vip genes. Our preliminary data using mutants lacking both Vip genes reveal these genes are key in signaling the energy status of the plant cell. Further, we have identified a possible mechanistic link between inositol pyrophosphate signaling and a major regulator of eukaryotic metabolism, the Sucrose non-fermenting related kinase 1 (SnRK1). Given the immediate need to understand and manipulate plant bioenergy, the long-term goal of this project is to understand how InsP6, InsP7 and InsP8 convey signaling information within the cell. We focus on these molecules in plants, but point out that our model and findings are applicable to understanding the InsP6 signaling hub in other eukaryotes. During the proposed project, we plan to address several unresolved questions pertaining to PPx-InsPs and energy by first adding to a preliminary kinetic model of this signaling pathway.

This project is sponsored by National Science Foundation (NSF).

CRISP Type 2: Collaborative Research Towards Resilient Smart Cities

Ismail Guvenc
08/15/2016 - 08/14/2019

Realizing the vision of truly smart cities is one of the most pressing technical challenges of the coming decade. The success of this vision requires a synergistic integration of cyber-physical critical infrastructures (CIs) such as smart grids, smart transportation, and wireless communication systems into a unified smart city. Such CIs have significant resource interdependencies as they share energy, computation, wireless spectrum, personnel (users, operators), and economic investments. Such resource sharing increases the proneness of such CIs to cascading failures. For example, the failure of a generator will cause a power outage for residential customers as well as an outage on portions of the wireless CI. This, in turn, can impact the platoons of vehicles connected to this communication CI. Protecting such CIs from failures requires instilling resiliency into the processes which manage their common resources. Resiliency is defined as the CIs’ ability to recover from failure by optimally allocating their resources over their nodes and connections. While there has been notable activity recently in improving the resiliency of CIs, these have been primarily motivated by singular and often catastrophic events related to weather, terrorism and other natural disasters. Also, most such efforts have been restricted to a single CI with only one interdependency between a communication and a physical component and do not explicitly account for the presence of humans that interact seamlessly with the CIs. In reality, smart cities require protecting multiple, interdependent CIs each of which is used by millions of users. The goal of this interdisciplinary research is to address this challenge by developing a holistic approach for optimizing the resiliency of a city’s interdependent CIs.

This research will lay the foundations of resilient smart cities by introducing a foundational framework for leveraging the CIs’ interdependencies to yield resilient resource management schemes cognizant of both technological and human factors. By bringing together researchers in cyber-physical systems, computer and network science, transportation engineering, security, behavioral economics, power systems, wireless networks, and psychology, this framework will yield theoretical and practical advances: 1) Rigorous mathematical techniques for delineating the interdependencies between CIs via a symbiotic mix of novel tools from graph theory, machine learning, and random spatial models; 2) Novel resilient resource management mechanisms that advance notions from powerful frameworks such as cognitive hierarchy theory, dynamic learning, and the Colonel Blotto game to enable optimized management of shared CI resources in face of failures stemming from agents of varying intelligence levels ranging from random events (wear-and-tear, natural disasters) to highly strategic attacks; 3) New behavioral models for characterizing the trust relationships between a smart city’s residents and the CIs; 4) Behavioral studies that provides guidelines on: a) how to influence the CIs’ users using communication messages conveyed over platforms to be developed and b) how such influence impacts the resiliency of the coupled CIs; and 5) Large-scale smart city simulator that exploits realistic CI data coupled with real-world experiments over four major smart grid, communication, and transportation testbeds, that will bridge the gap between theory and practice.

This project is sponsored by Florida International University.

Investigations On Current And Future 3GPP Channel Models And The Evaluation Of Various Existing MIMO Techniques With These Channel Models

Ismail Guvenc, Yavuz Yapici
08/15/2016 - 04/30/2020

This new supplement aims to extend the earlier measurements and analytical studies into metasurface reflectors. In particular, we will carry out measurements using metasurface reflectors in indoor/outdoor scenarios, and compare the performance with the case when only standard metallic reflectors are used. Frequency band of interest is 28 GHz. We aim to do measurements in the lab environment as well as outdoor settings in NCSU campus.

This project is sponsored by DOCOMO Innovations, Inc..

Magnetoelectrics and Spinorbitronics in Topological Heterostructures and Superlattices

Ki Wook Kim
08/09/2016 - 11/08/2019

As part of the UCLA led team, we propose to explore the nontrivial spin textures and dynamics in strongly spin-orbit coupled materials and their heterostructures, particularly with topological insulators (TIs) and emergent two-dimensional transition-metal dichalcogenides (TMDs). The specific research objectives include: (1) spin textures, spin-orbit torque, and THz spin-dynamics in the TIs and the related material combinations, and (2) strong spin-orbit coupling and the resulting spin-valley textures in the TMD based structures. In the first task, novel spin correlated phenomena and innovative applications will be examined primarily in the TI/magnet systems to take advantage of the spin-momentum entwinement in the TIs and the strong exchange interaction with the neighboring magnetic materials. The focus will be on the microscopic modeling of antiferromagnet dynamics, spin wave generation in the THz, and the domain wall motion (including the skyrmions) through electrical control of spin-orbit torque. In the study of the TMD based structures, the unique properties of this system enabled by the spin-valley interlock will be examined from three different aspects to broadly exploit the possibilities they offer; i.e., magneto-optic effect including coherent THz radiation, electrical control of spin-valley polarization, and spin/charge density wave generation. The physical phenomena as well as their applications originating from the nonlinear dynamics and textures will be examined theoretically based on multiscale treatments including the micro-magnetic simulations and first principles calculations. The latter, ab initio method based on the density functional theory formalism will be needed to accurately characterize emergent material properties under such conditions as doping, strain, or chemical functionalization. The analytical effort will be pursued in strong collaboration with the concurrent experimental investigation.

This project is sponsored by University of California - Los Angeles.

10kV SiC Integrated VSD Motor Drive

Subhashish Bhattacharya
08/01/2016 - 07/31/2020

The project team will develop an integrated MV SiC VSD drive and high speed motor for oil and gas industry compression system applications. To meet the power density and environmental requirements of an integrated drive, the team will develop and package a variable frequency drive topology utilizing 15kV SiC MOSFET devices, high-frequency inductors and dv/dt filters, and other customized peripherals including high temperature capacitors. The team will develop drive architectures, device controls and electrical integration techniques to take advantage of high speed SiC switching. Eaton’s state-of-the-art MV converter packaging and innovative integrated cooling concepts will produce a design capable of being fully integrated into a high speed motor with hermetically sealed enclosure. The team will use advanced machine design techniques to identify best candidate motors for integration based on system and motor performance goals, TRL, drive integration requirements and will develop solutions to address identified technology gaps.

This project is sponsored by Eaton Corporation.

A Path Towards III-Nitrides-Based Superjunction Devices

Zlatko Sitar, Leda Lunardi
08/01/2016 - 07/31/2020

The proposed research will extend the applicability of wide bandgap semiconductors beyond the traditional limits imposed by the unipolar (Baliga’s) figure of merit by demonstrating a path to superjunction structures based on novel doping and defect control processes. This will lead to a new generation of devices that take advantage of the expected capabilities of III-nitrides but are not limited by doping or implantation technology. Superjunction device structures based on AlGaN are proposed where they exploit the doping selectivity observed in different III-nitride polar domains and the lateral polar patterning technology developed at the WideBandgaps Laboratory at NCSU. In addition, further control of point defects will be realized through the use of Fermi level control schemes based on engineered illumination by the use of UV (blue) lasers surface selective during the growth of the device structure. Such structures will eventually allow for significant breakdown voltages exceeding 5 kV and significant low on-resistance, beyond the expected rated BFOM. This research will provide for a transformative and disruptive technology for power electronics and also provide a breakthrough technology for other applications such as efficient deep UV emitters for water purification. The successful demonstration of such disruptive technology would revolutionize energy switching and transmission, energy storage, and related applications in electrical motor drives and other power intensive applications within the US. As such, the White House has recognized the need to build America’s leadership in this technology as part of the manufacturing innovation institutes. In general, this research will directly lead to materials that will be used for applications that deal with the preservation and extension of natural resources by: (1) allowing for the efficient 
use and transmission of electrical energy, (2) availability of clean potable water through 
disinfection by the use of UV, and (3) the detection of pollutants and other effluents. This 
program will provide the opportunity to educate a Ph.D. student with support from an undergraduate student on the growth and characterization of wide bandgap materials while participating with the group’s international collaborators network.

This project is sponsored by National Science Foundation (NSF).

Collaborative Research: A Visual System for Autonomous Foraminifera Identification

Edgar J Lobaton
08/01/2016 - 07/31/2019

Paleoceanography, among other research fields, depends crucially on ubiquitous ocean dwelling single celled organisms called foraminifera. Undergraduate workers are often employed to pick several thousands of specimens from ocean sediments for each study. Depending on deposition rates and abundance of the species, such manual processing can become tediously repetitive with little intellectual motivation for the undergraduate workers, and time and cost-prohibitive for research scientists. The proposed project aims to develop a completely autonomous system for visual identification of foraminifera. This system will be compatible with existing off-the-shelf microscopes, and will utilize pattern recognition tools that will be made available to the entire scientific community. This project has the potential to enable robotic systems that can perform autonomous picking of foraminifera samples.

This project is sponsored by National Science Foundation (NSF).

I/UCRC for Advanced Electronics Through Machine Learning (CAEML)

Paul D. Franzon, William R. Davis, & Brian Allan Floyd
08/01/2016 - 07/31/2021

The purpose of this request is to request an REU Supplement to our IUCRC Award.

This project is sponsored by National Science Foundation (NSF).

NYPA Convertible Static Compensator (CSC) Control System and Development of a CS Real-Time Digital Simulation Model

Subhashish Bhattacharya
08/01/2016 - 07/31/2019

The objective is to develop a detailed RTDS model of the CSC that will precisely recreate the functionality of the NYPA CSC. The RTDS model shall replace the analog TNA system for modeling and simulation purposes of the CSC that require real-time simulation of the CSC device or hardware-in-the-loop simulation and testing. A hardware-in-the-loop test of the new control system will be performed using the verified RTDS model. All results will be validated against the final commissioning and test results of the NYPA CSC from 2004.

This project is sponsored by New York Power Authority.

SHF:Small:Enabling Efficient Context Switching and Effective Latency Hiding in GPUs

Huiyang Zhou
08/01/2016 - 07/31/2019

This project investigates novel ways to enable efficient preemption and effective latency hiding in single-instruction multiple-thread (SIMT) processors such as graphics processing units (GPUs). With the advent of the big data era, there is an increasing demand for data processing. Given their high computational throughput and high memory access bandwidth, GPUs have been widely used, ranging from smartphones, cloud servers, to supercomputers. Although virtualization has been introduced to enable GPUs as shared resource, significant hurdles remain. First, due to the high number of concurrent threads, GPUs have a large context size. Consequently, state-of-art GPUs resort to techniques like draining to complete the actively running threads before context switching. This may incur significant delay and fail the required quality of service (QoS). Second, it is very common that applications fail to fully utilize the computational resource and achieve the peak performance. There are two fundamental reasons. (a) Each thread requires a non-trivial amount of resource. Therefore, only a limited number of threads can run concurrently even if applications themselves have abundant thread-level parallelism. Without a sufficiently high number of threads, the latency hiding capability of fine-grain multithreading is severely impaired. (b) Long latency operations, off-chip memory accesses in particular, need a very high number of concurrent threads to hide their latency. The on-chip resources, however, cannot accommodate such large numbers of concurrent threads.

This project is sponsored by National Science Foundation (NSF).

mm/sub-mm Wave Compressive Sensing Imaging

David Ricketts, Dror Zeev Baron
07/01/2016 - 06/30/2020

mm/sub-mm wave compressive sensing on diffraction limiting affects.

This project is sponsored by National Science Foundation (NSF).

“Demonstration of a Medium Voltage Power Module for High Density Conversion” Task 4.6:Pwr Amer-Hopkins- BP-2

Douglas C Hopkins, Ola L. Harrysson, & Subhashish Bhattacharya
06/15/2016 - 06/30/2020

The SuperCascode Power Module (SCPM) is a new approach to high voltage switches introduced by USCi. Inc. The SCPM uses a series string of SiC JFETs in a cascode configuration switched with a Si MOSFET. This one year project shall develop a medium voltage (MV) 6.5kV/50A/100A SCPM with extension to 200A, and a continuous Full-Power emulation Test Platform (FPTP) based on the ERC concept, which shall demonstrate full-power in-situ performance of the SCPM.

This project is sponsored by NCSU PowerAmerica: Next Generation Electronics Manufacturing Innovation Institute.

Multidisciplinary Graduate Training in Advanced Technologies for High Yield Sustainable Agriculture

Jeffrey G. White, Colleen J. Doherty, & Ronnie W. Heiniger
06/15/2016 - 12/14/2020

Agriculture is the primary economic activity undergirding human survival and quality of life and global economic development. To grow agricultural productivity we will establish an interdisciplinary graduate training program to address Plant Production within the Targeted Expertise Shortage Area (TESA) of Food Production. The goals of this program are: 1) comprehensively train three PhD fellows, each in a core discipline within plant production with cross-training in complementary areas; 2) provide experiential training within a technology rich, multidisciplinary research and Extension platform; and 3) graduate students proficient at integrating computational, environmental, biological and physical data into decision tools for increased yield and economic sustainability. This will be achieved through: recruitment of top tier, diverse Fellows; intensive advising and mentoring by exemplary faculty; outstanding academic, international, and industry-based research opportunities; leadership and professional development training, and internships with local Agbiotech companies. Fellows’ research will be grounded in the innovative research platform (AMPLIFY), a strategic industry-academia- producer partnership conducting interdisciplinary multi-scale systems research to advance high- yield sustainable agriculture to meet our world’s growing food requirements. Success will be measured by: 1) diversity of recruits; 2) presentations at professional conferences and publication in refereed journals; 3) timely degree completion; and 4) successful placements in industry, academia, or government appropriate to TESA. This NNF is relevant to the USDA/NIFA Challenge Area, Plant Production. Measurable impacts on TESAs include a more diverse scientific workforce trained in skills necessary to address complex challenges facing agriculture.

This project is sponsored by US Dept. of Agriculture (USDA) - National Institute of Food and Agriculture.

Collaborative Research: Modular Multilevel Converter with Parallel Connectivity — Novel Topology, Control, and Applications

Srdjan Miodrag Lukic
06/01/2016 - 05/31/2020

The Modular Multilevel Converter (MMC) has become established in high voltage and power applications due to its ability to split the system voltage into lower module voltages, its high efficiency, and its unmatched output power quality. Despite these advantages, however, the MMC has not made significant inroads in low and medium power applications. The key reasons are the complex monitoring required to ensure module balancing and the inefficient utilization of modules at voltages below the system maximum. Both of these disadvantages stem from the limitation that MMC modules can only be connected in series or bypassed. Addressing this limitation, we have recently proposed and demonstrated a new family of converters that extend the MMC to provide parallel connectivity of modules. Compared to the MMC, the novel modular multilevel series parallel converter (MMSPC) increases efficiency for the same total silicon and allows charge transfer between modules, akin to switched-capacitor topologies, thus drastically simplifying module balancing. This added functionality could open an entirely new space of low, medium, and high voltage applications of multilevel converters.

This project is sponsored by National Science Foundation (NSF).

Enabling High Penetration of Distributed PV through the Optimization of Sub-transmission Voltage Regulation

Ning Lu, Alex Q. Huang
05/18/2016 - 09/30/2019

Reverse power flows and variable outputs of solar generation resources could cause temporal and spatial voltage variations in the power network. Such variations can lead to exceedance of voltage limits set by NERC voltage and reactive control standard VAR-001-4 at the sub-transmission level and ANSI
standards at the distribution level. Voltage regulation devices deployed today are operated to cope mainly with system load changes. Their settings are usually determined on a seasonal basis. The location, capacity, and operation of these devices are not designed and coordinated for managing the real-time
variations caused by distributed solar photovoltaics (PVs). As a result, over- or under- voltage problems can happen more frequently, especially in light load seasons such as spring and fall. Those phenomena have already been observed in high solar penetration areas, such as Hawaii and Southern California. PNNL will partner with North Carolina State University (NCSU), GE Global Research, One-Cycle Control Inc. (OCC) and Duke Energy to develop a Coordinated Real-time Sub-Transmission Volt-Var Control Tool (CReST-VCT) to optimize the use of reactive power control devices to stabilize voltage
fluctuations caused by intermittent PV outputs. In order to capture the full value of the Volt-Var optimization, we propose to couple this tool to an Optimal Future Sub-Transmission Volt-Var Planning Tool (OFuST-VPT) for short- and long-term planning. Together, the real-time control and planning tools
will remove a major roadblock in the increased use of distributed PV.

This project is sponsored by Pacific Northwest National Laboratory.

Resilient Information Architecture Platform for the Smart Grid (RIAPS)

Srdjan Miodrag Lukic
04/04/2016 - 07/03/2019

The goal of the Resilient Information Architecture Platform for the Smart Grid (RIAPS) project is to design, prototype, document, and evaluate via concrete applications a software platform for use in various networked computing nodes attached to the Smart Grid.
The Smart Grid will run on software that depends on a software platform. Just as a revolution in Smartphones was started by Android that enabled all sorts of software ‘apps’ to run on a wide variety of devices, our vision is that the same principle applies to the development of the Smart Grid, and the design, specification and prototyping of such an open software platform is essential for the growth and proliferation of the system.

This project is sponsored by Vanderbilt University.

CAREER: Data Representation and Modeling for Unleashing the Potential of Multi-Modal Wearable Sensing Systems

Edgar J Lobaton
04/01/2016 - 03/31/2021

The objective of this proposal is to develop a computational framework that integrates statistical and computational geometric data analysis techniques for the processing, analysis and representation of patterns in order to unleash the potential of physiological and environmental multi-modal wearable sensing health systems for continuous monitoring and tracking of human wellness and physiological state. To accomplish this objective, this proposal will: (1) develop algorithms for the concurrent modeling of physiological, kinematics and environmental states for inference purposes; (2) develop techniques to transform models between different sensing systems in order to make information sharing compatible across platforms; and (3) develop techniques to maximize the impact on the behavior of individuals by elaborating on schemes for data representation. These techniques will empower users and medical practitioners to understanding, analyze, and make decisions based on patterns present in the data.

This project is sponsored by National Science Foundation (NSF).

Sunshot National Laboratory Multiyear Partnership (SUNLAMP) Combined PV/Battery Grid Integration with High Frequency Magnetics Enabled Power Electronics

Subhashish Bhattacharya
03/01/2016 - 09/30/2019

The PI (Subhashish Bhattacharya) NCSU is responding to the NETL RFI number: DE-FOA-0001314 Technical Collaboration Opportunities # 3 for the above titled DOE SunShot based SuNLaMP proposal.
In this proposal NETL proposes to develop new power electronics converters using high frequency semiconductors and magnetics for 13.8kV, 60Hz grid connection of distributed photovoltaics (PV) in a modular DC-DC and/or DC-AC cascading inverter designs.

This project is sponsored by NETL (National Energy Technology Laboratory).

CAREER: Bio-electro-photonic Microsystem Interfaces for Small Animals

Alper Yusuf Bozkurt
02/15/2016 - 01/31/2021

The goal of this project is to develop novel biophotonic devices and systems for studying global hemodynamic parameters in small animals. Such a system would respond to the critical need for small, wireless, minimally invasive systems for recording key physiological parameters during daily living activities in both laboratory environments and natural habitats without disturbing natural behavior and requiring a surgical implantation.

This project is sponsored by National Science Foundation (NSF).

NeTS: Small: Collaborative Research: On the Ontology of Inter-Vehicle Networking with Spatio-Temporal Correlation and Spectrum Cognition

Wenye Wang
10/01/2015 - 09/30/2019

Vehicle networks have been playing an increasing role in driving safety, network economy, and people’s daily life. While vehicle networks have received tremendous attentions, the existing research is primarily focusing on the performance study of vehicular networks by taking three assumptions: there exists a vehicle network through vehicle-to-vehicle and/or vehicle-to-infrastructure communications, there exists a finite path in the network between any two vehicles, and there exist attainable wireless channels for communications. In view of upcoming boom of mobile applications over vehicular networks in practice and wide-range deployment of autonomous driving vehicles in the near future, the validity of these assumptions is questionable. In this project, we propose to address four interrelated but equally important issues towards building blocks of a theoretical foundation, so called ontology of inter-vehicle networking, which are the composition of inter-vehicle networks, discovery of neighboring vehicles through spectrum cognition, coverage of messages in finite and large-scale networks, and robustness properties of inter-vehicle networks. The objective is to investigate fundamental understanding and challenges of inter-vehicle networking, including theoretical foundation and constraints in practice that enable such networks to achieve performance limits.

This project is sponsored by National Science Foundation (NSF).

© NC State University. All rights reserved.

Contact Webmaster  |   Accessibilty   |   Privacy   |   myECE

© NC State University. All rights reserved.