Our Research Projects

Project runs from 08/16/2020 to 09/30/2022

This project explores advanced architectural designs that eliminate side channel attacks on memristor-based memory architectures.

Project runs from 07/31/2020 to 07/31/2022

Integration of multiple generation sources, including legacy devices is a difficult problem due to multiple causes: lack of advanced control algorithms, engineering processes for integrating generation technology, and the inherent complexities of system integration. Forming networked microgrids out of these heterogeneous power sources is a further challenge, due to the varying dynamics of the resources, different communication protocols used and the required redesign of the protection systems. Our aim is to demonstrate how a solution based on distributed computing techniques, advanced software engineering methods and state-of-the-art control algorithms can provide a scalable and reusable solution to the problem, yielding a highly configurable Integrated Microgrid Control Platform (IMCP) that can be reused across many facilities.

Project runs from 08/03/2020 to 07/31/2021

Emerging Non-Volatile Memories (NVMs) promise convergence of memory and storage into a single system that is both fast and persistent. Existing security functions for storage systems were designed for slower storage devices, which create a performance bottleneck for faster NVMs. This research will investigate high performance security solutions for NVM based storage systems.

The first research thrust will focus on encrypting data for emerging NVMs. The second thrust investigates implementation of auditing mechanisms for NVM based storage systems.

The proposed project will train graduate and undergraduate students on architecting secure systems. The results from this research will inform several undergraduate and graduate courses. Students from underrepresented groups will be encouraged to participate in this project. The results will be published in reputed conferences and journals.

Project runs from 08/01/2020 to 07/31/2023

The proposed project will apply risk segmentation, adaptive credit scoring and network-based portfolio analysis techniques from financial engineering and risk management for risk analytics of power systems at both asset and system levels. At the asset level (Thrust 1), the project will introduce risk segmentation of an asset’s throughput by applying tranching similar to collateralized debt obligations. The risk-free to most risky tranches will be assessed for their risk profile in terms of risk scores taking into account the variability of the renewable resource (wind or solar), presence of storage units or services that they may be equipped/associated with, and the asset’s locational specification. This risk scoring will be designed to be adaptive based on system level (Thrust 2) feedback at different contractual time-scales, starting from sub-seconds to tens of minutes, to determine asset suitability as an energy, regulation, spin, non-spin, or replacement reserve. Novel copula-based probabilistic risk models will be developed for the joint correlation structures between different contract tranches of assets for asset and system level risk assessment.

Project runs from 09/01/2020 to 12/31/2022

As power electronics systems on the grid are increasing due to integration of new distributed energy resources couple with the evolution of loads such as EV charging, smart homes, and server farms, there is increased pressure on the utilities to interface, control, coordinate and optimize these various systems. This work supports the GMLC 2019 project entitled “Multi-Port Modular Medium-Voltage (M3) Transactive Power Electronics Energy Hub.” The overall intent of this project is to design, develop, and demonstrate foundational technologies and capabilities for multiport power electronics energy hubs (a.k.a. HUB) that can serve as intelligent devices to coordinate and control several different sources and loads.
As part of this project, NCSU will support two primary aspects of the HUB hardware. The first is to duplicate a 50 kW isolated DC-DC converter based on the high frequency bi-directional isolated 2 port dc-dc power stage developed under “Combined PV and Battery Grid Integration Enabled Through High Frequency Magnetics: (SuNLaMP) GMLC (31004).” The second is the development and demonstration of a 3.3 kV H-bridge power stage to support the MV HUB concept. Both pieces of hardware will be delivered to ORNL for integration and testing into the larger M3PE HUB configuration.

Project runs from 07/30/2020 to 07/29/2023

We will design and fabricate micro-electrode arrays for the subcutaneous, electrochemical measurements of LH. The micro-electrode arrays will be integrated with a wireless, wearable monitoring system. LH is a hormone produced by gonadotropic cells, and in females, an acute rise in LH triggers ovulation.

Project runs from 09/01/2020 to 08/31/2023

1.7 million Americans rely on Power Mobility Devices (PMDs) – power wheelchairs and electric scooters – to improve their mobility. However, they still travel less than users of manual wheelchairs and much less than people without disability, where sometimes only 2% of that distance occurs outdoors. Users and caregivers consistently report the energy constraints of PMD’s batteries as one of the top reasons for limited away-from-home mobility. A collaborative research team from NCSU (Raleigh) and UNC (Chapel Hill) are partnering with a group of stakeholders to pilot a public charging infrastructure and cyber-information system to support outdoor use of power mobility devices, to improve the mobility and inclusion of their owners. The project objectives are to 1) design, develop, and test a pilot public physical charging network accessible for PMD charging; 2) make the charging stations real-time IoT-connected through Google Maps services; 3) build smart energy monitoring hardware to track the PMD energy consumption and driving parameters, 4) develop a cloud-based, data-driven energy consumption prediction algorithm to enable route planning, 5) write a Best Practice Protocol to alleviate scaling up the charging network, and 6) increase the awareness of the general population regarding the needs of people with disabilities and aging adults. The anticipated project outcomes are: (1) the PMD users will be able to successfully use public charging stations and charging apps; (2) the overall distance traveled by PMD will increase for 10%; (3) the average participation of outdoor miles in totals PMD miles traveled will increase; (4) the life-time of PMD batteries will increase. The project will generate the following products: (1) an operational pilot charging infrastructure installed in Downtown Raleigh, (2) a fully functional charging app for managing the charging process, (3) cloud-located AI-based software capable of estimating PMD energy consumption for a specified route, and (4) Best Practice Protocol instructions for further expansion of charging network.

Project runs from 01/01/2021 to 12/31/2023

We propose a novel sensor system with accompanying data analytics to explore the capability of wearable multimodal sensors to address the short-comings of the traditional polysomnography systems. If successful, this project will lead to improved capacity to carry out sleep research and to detect and treat sleep disorders. The miniaturization and low power consumption will pave the way for rapid adoption and deployment of these systems for home-use in real-world settings.

Project runs from 10/01/2020 to 09/30/2023

Minimizing crop loss and increasing output, across the food supply chain, will increase the economic viability of US growers and the global economic competitiveness of industry and stakeholder partners. We have assembled a diverse team across different National and International Universities with faculty that have track records of convergent research, education, and outreach. We will be well positioned to implement a Networks of Networks with diverse backgrounds, ethnicities, genders, experiences, and disciplines to drive research and innovation. Students and postdocs will be exposed to hands-on learning, on-farm technology training, cooperative extension, commercialization, industry engagement, and transdisciplinary education to create a highly trained workforce that is equipped to address food security and safety challenges.

Project runs from 08/15/2020 to 08/14/2022

Cirrus Logic will support a Fellowship in mixed signal design.

Project runs from 10/01/2020 to 09/30/2023

There has been an explosive growth in the number of Internet-connected devices. The end-device users have also built a stack of rich and complex networks, derived from their social, personal and work groups. The prolific connections to end-devices and users, however, can be exploited as devastating vehicles for malware and worm attacks. Since exploiting the network connectivity lies at the heart of malware distribution, it becomes crucial to understand how the underlying network structure affects the malware propagation. Despite abundant literature on epidemic modeling and analysis, there is still a huge gap between theory and practice. This project aims to bridge the gap to better understand and combat epidemic spreading on large-scale networks with realistic cost constraints.

This collaborative project brings together investigators from Florida Institute of Technology and North Carolina State University to investigate the following inter-related research thrusts. It will (1) develop a theoretical framework to fully characterize the transient dynamics of epidemic spreading on a general graph (as opposed to a complete graph) to estimate and predict the likelihood of each node being infected for the future time, (2) develop a suite of readily usable algorithms to mitigate the spread of an epidemic to the extent possible under realistic constraints, and (3) develop a set of algorithms for efficient estimation and inference of network and epidemic parameters from incomplete and noisy data of epidemic cascades. This project could potentially have a high impact on a vast range of multi-disciplinary areas and applications where the study of epidemics has been necessary and crucial, including epidemiology, percolation in physics and chemistry, rumor spreading, information cascades, viral marketing, and spread of misinformation and fake news.

Project runs from 08/17/2020 to 04/30/2021

HDF5 is designed to store and manage high-volume and complex science data and has become the leading I/O middleware solution at DOE supercomputing centers. As upcoming exascale supercomputers are using accelerators, such as graphical processing units (GPUs), for improving the performance of computing, data must be moved efficiently between storage and accelerators. To perform efficient parallel I/O in accelerated computing nodes for moving data between multiple GPUs and the parallel file system using node-local storage devices and network interconnects, this project will extend asynchronous I/O. In this project, Dr. Michela Becci and her student will work with us in identifying I/O benchmarks representative of ECP applications and profiling their current performance. The project will then update the designs of asynchronous I/O for using GPUs and node-local storage on a compute node.

Project runs from 08/10/2020 to 03/24/2021

The project explores novel architectural support for NVM integrity, confidentiality and availability protections.

Project runs from 01/01/2021 to 12/31/2023

Wireless systems with different radio access technologies (RATs)nare becoming packed tightly in the space of radio spectrum. The carrier frequency and channel bandwidth of these systems, however, are drastically different across the spectrum domain, e.g., the IEEE 802.11 family that operates at 900 MHz, 2.4/5 GHz, and 60 GHz (mm-wave) bands, the 3GPP 5G family that spans 6-100 GHz, and more. Therefore, radio spectrum, which has long been identified as a scarce resource, will be more crowded and diversified than ever. Swift and effective spectrum sharing requires enhanced capability and increased intelligence at the wireless devices, from innovative transmitter and receiver technologies at the physical layer, to multi-band spectrum sensing across physical and MAC layer; from mapping spectrum slices for each access request, to radical modification of medium access control (MAC) protocols. Altogether, there is a need to support a myriad of heterogeneous devices that run diverse communication standards over different frequency bands to achieve efficient spectrum and energy utilization in such huge, dynamic and disparate systems.
This project mitigates the incoherent and disassociated frequency bands of the multi-RAT coexisting environments by exploiting the potential of cross-layer design from the circuits of transmitter and receiver, to the MAC layer with an innovative MAC-on-MAC spectrum control plane. This project has four major thrusts: (i) design of innovative transmitter and receiver techniques for energy-efficient multi-band spectrum monitoring, by using custom single-chip ultra-broadband (1-8 GHz) bio-inspired spectrum sensors to create a multi-band sensing solution that includes both sub-6 GHz and emerging mm-wave bands; (ii) methods to acquire complete spectrum occupancy information with a limited number of measurements from the proposed multi-band spectrum sensing circuits by exploiting matrix completion for low-cost, accurate and scalable monitoring through a learning-based sequential scheme; (iii) algorithms of obtaining a sorted ranking of paths that map a data flow to a range of spectrum slips by modeling spectrum-flow-RAT domains, finding the set of unoccupied spectrum slices, sorting out multiple recommendations from neighboring SAP control entities; (iv) creating MAC-Flow, a flow based network protocol that is capable of handling networking demands from both upper and lower layer, for both traditional user frames and for MAC-on-MAC controller processed frames for system-level performance evaluation

Project runs from 10/01/2019 to 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

Project runs from 06/15/2020 to 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.

Project runs from 09/01/2020 to 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.

Project runs from 08/10/2020 to 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.

Project runs from 08/01/2020 to 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

Project runs from 09/01/2020 to 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.