ECE Assistant Professor Chung-Tse Michael Wu is the recipient of a new award from the Army Research Lab (ARL) for the project “Power Efficient Metamaterial Intelligent Surfaces and Antenna Arrays using Liquid Metal-based Heterogeneous Integration.”  This project is funded at $200,000 for the first year with an option to extend to $750,000 over three years.

 

Metamaterials (MTMs) are artificial structures with unusual properties, such as negative index of refraction, negative permittivity and permeability, which typically cannot be found in nature. Owing to these exotic electromagnetic (EM) properties, the concept of MTMs has been adopted to develop various guided and radiated wave structures with enhanced functionalities. In particular, 2D-MTMs or metasurfaces have recently gained much attention due to the capability of manipulating the transmission and reflection characteristics of EM waves. The proposed research project aims to create a new category of liquid metal based reconfigurable MTM intelligent surfaces as well as metasurface antenna arrays for next generation sensing and communication. By incorporating liquid metal into soft materials, the resulting MTM intelligent surfaces and metasurface antenna arrays can be made stretchable and bendable, thereby allowing themselves to be deployed onto conformal platforms.

 

Congratulations, Michael!

 

ECE Professor Emina Soljanin is the recipient of a new NSF award for the research project titled "Redundancy for Storage in the Edge."  This is a three-year project  in partnership with Technion, Israel that is supported under the NSF US-Israel Binational Science Foundation (BSF) Collaborative Research Opportunities. Rutgers' share of the award is $500,000.

 

In this project Professor Soljanin will design storage schemes to facilitate emerging Internet of Things (IoT) ecosystems. The IoT revolution is driven by a surge of applications based on intelligent edge devices, such as smart cities and homes, autonomous vehicles, online video gaming, virtual and augmented reality, and machine learning. The back end of these systems is a central service where a large amount of data generated by edge devices is continuously collected, aggregated, and analyzed. Unfortunately, traditional cloud services cannot provide performance guarantees that the latency-critical applications require, mainly due to round-trip times which can take several hundreds of milliseconds. Thus, such applications will likely rely on Edge services-an emerging technology tightly coupled with 5G cellular networks. This project focuses on enabling unstable edge nodes to collectively provide a reliable storage service for unpredictable user demands. Towards this goal, redundant storage schemes for edge systems will be designed and evaluated.

 

More details on the project can be found on the NSF page here.

 

Congratulations Emina!