System Bits: July 10


Light waves run on silicon-based chips Researchers at the University of Sydney’s Nano Institute and Singapore University of Technology and Design collaborated on manipulating light waves on silicon-based microchips to keep coherent data as it travels thousands of miles on fiber-optic cables. Such waves—whether a tsunami or a photonic packet of information—are known as solitons. The... » read more

Power/Performance Bits: July 10


Wearable heart monitoring Researchers at the University of Texas at Austin developed a lightweight, stretchy heart monitoring patch that can be worn externally. Along with being easy to wear, the graphene-based 'e-tattoo' is more accurate than existing electrocardiograph machines, according to the team. The e-tattoo measures cardiac health using both electrocardiograph and seismocardiograph... » read more

Will Open-Source EDA Work?


Open-source EDA is back on the semiconductor industry's agenda, spurred by growing interest in open-source hardware. But whether the industry embraces the idea with enough enthusiasm to make it successful is not clear yet. One of the key sponsors of this effort is the U.S. Defense Advanced Research Projects Agency (DARPA), which is spearheading a number of programs to lower the cost of chip ... » read more

Power/Performance Bits: May 14


Detecting malware with power monitoring Engineers at the University of Texas at Austin and North Carolina State University devised a way to detect malware in large-scale embedded computer systems by monitoring power usage and identifying unusual surges as a warning of potential infection. The method relies on an external piece of hardware that can be plugged into the system to observe and m... » read more

System Bits: April 16


Characterizing 2D borophene Researchers at Rice and Northwestern universities collaborated on a method to view the polymorphs of 2D borophene crystals, providing insights into the lattice configurations of the two-dimensional material. Boris Yakobson, a materials physicist at Rice’s Brown School of Engineering, and materials scientist Mark Hersam of Northwestern led a team that not only d... » read more

EUV Arrives, But More Issues Ahead


EUV has arrived. After decades of development and billions of dollars of investment, EUV lithography is taking center stage at the world’s leading fabs. More than 20 years after ASML's extreme ultraviolet lithography research program began, and nearly a decade after its first pre-production exposure tools, the company expects to deliver 30 EUV exposure systems in 2019. That is nearly doubl... » read more

System Bits: March 11


Cryptography IC for the IoT Massachusetts Institute of Technology researchers report their development of a cryptographic circuit that could be used to protect low-power Internet of Things devices when quantum computing takes hold. [caption id="attachment_24144905" align="alignleft" width="300"] Image Credit: MIT[/caption] The research team presented a paper at the 2019 International Sol... » read more

The Good And Bad Of 2D Materials


Despite years of warnings about reaching the limits of silicon, particularly at leading-edge process nodes where electron mobility is limited, there still is no obvious replacement. Silicon’s decades-long dominance of the integrated circuit industry is only partly due to the material’s electronic properties. Germanium, gallium arsenide, and many other semiconductors offer superior mobili... » read more

Power/Performance Bits: Jan. 23


Atomristors for thin memory Engineers at The University of Texas at Austin and Peking University developed a thin memory storage device with dense memory capacity. Dubbed "atomristors," the device enables 3-D integration of nanoscale memory with nanoscale transistors on the same chip. "For a long time, the consensus was that it wasn't possible to make memory devices from materials that were... » read more

System Bits: Sept. 12


Neural network cautionary tale As machine learning and neural networks proliferate widely today, there is a need to exercise caution in how they are employed, according to Stanford University researchers Michal Kosinki and Yilun Wang. In a study conducted recently, they have shown that deep neural networks can be used to determine the sexual orientation of a person, and caution that this ma... » read more

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