Engineers and scientists at The University of Texas at Austin and the AMOLF institute in the Netherlands have invented the first mechanical metamaterials that easily transfer motion effortlessly in one direction while blocking it in the other, as described in a paper published on Feb. 13 in Nature. The material can be thought of as a mechanical one-way shield that blocks energy from coming in but easily transmits it going out the other side.
The National Science Foundation (NSF) has awarded a four-year, $2 million grant to Andrea Alù of the Cockrell School of Engineering at The University of Texas at Austin to break the conventional ways in which light and acoustic waves propagate.
As communication systems embrace ever wider bandwidths and the FCC seeks to codify next-generation standards, Analog-to-Digital-Converters (ADCs) struggle to meet rate, resolution and power requirements for these systems. The massive antenna arrays under consideration for next-generation wireless, which include tens or even hundreds of receiver channels, only exacerbate the problem.
Prof. Michael Orshansky and Prof. Sriram Vishwanath of the Department of Electrical and Computer Engineering in The University of Texas at Austin's Cockrell School of Engineering have received a research grant as part of the Secure, Trustworthy, Assured and Resilient Semiconductors and Systems (STARSS) program. STARSS is a joint program created by the National Science Foundation (NSF) and Semiconductor Research Coporation (SRC).
Reciprocity is a general symmetry property that applies to the vast majority of materials. If an antenna transmits towards a specific direction, it must also receive signals from that same direction. To protect sources and improve communication systems, it is desirable to build components not bound by reciprocity requirements that can transmit and receive signals in the same channel without interference.
As the adoption of Electronic Health Records (EHRs) increases in the USA, the complexity of EHR data is growing dramatically. EHR data now covers diverse information about patients, including diagnosis, medication, lab results, genomic information and clinical notes. However, such large volumes of information do not readily provide accurate and succinct patient representations for effective and customized healthcare.