Power/Performance Bits: Jan. 13


Ferroelectric memory Researchers at the Moscow Institute of Physics and Technology and North Carolina State University developed a ferroelectric memory cell and a method for measuring the electric potential distribution across a ferroelectric capacitor, an important aspect of creating new nonvolatile ferroelectric devices. The team's new ferroelectric memory cell is made from a 10nm thick z... » read more

Power/Performance Bits: Jan. 7


Ferroelectric FET Researchers at Purdue University developed a ferroelectric transistor capable of both processing and storing information. The ferroelectric semiconductor field-effect transistor is made of alpha indium selenide, which overcomes the problem of ferroelectric materials not interfacing well with silicon. “We used a semiconductor that has ferroelectric properties. This way tw... » read more

Power/Performance Bits: Oct. 15


Probabilistic computing Researchers at Purdue University and Tohoku University built a hardware demonstration of a probabilistic computer utilizing p-bits to perform quantum computer-like calculations. The team says probabilistic computing could bridge the gap between classical and quantum computing and more efficiently solve problems in areas such as drug research, encryption and cybersecurit... » 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: June 18


Multi-value logic transistor Researchers at the University of Texas at Dallas, Hanyang University, Gwangju Institute of Science and Technology, Yonsei University, Kookmin University, and Ulsan National Institute of Science and Technology developed and fabricated a transistor capable of storing intermediate values between 0 and 1. Such a multi-value logic transistor would allow more operations ... » read more

System Bits: June 4


Thin films for quantum computing Researchers at Los Alamos National Laboratory report their development of two-dimensional tungsten/selenium thin films that can control the emission of single photons, potentially useful in quantum technologies. “Efficiently controlling certain thin-film materials so they emit single photons at precise locations—what’s known as deterministic quantum em... » read more

Power/Performance Bits: Mar. 5


Solar chemical manufacturing Researchers at RMIT University, CSIRO Manufacturing, and University of Melbourne developed a nano-enhanced material that can capture 99% of light and use it to power chemical reactions. One of the world's biggest energy users, the chemical manufacturing industry accounts for about 10% of global energy consumption and 7% of industrial greenhouse gas emissions. In th... » 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

System Bits: Jan. 22


Toward more trusted microelectronics David Crandall, an associate professor in Indiana University Bloomington’s School of Informatics, Computing and Engineering, is collaborating with other researchers through the Indiana Innovation Institute (IN3) to work on technology challenges for private industry and the U.S. Department of Defense. Crandall is currently tackling trusted microelectron... » read more

Power/Performance Bits: Jan. 22


Efficient neural net training Researchers from the University of California San Diego and Adesto Technologies teamed up to improve neural network training efficiency with new hardware and algorithms that allow computation to be performed in memory. The team used an energy-efficient spiking neural network for implementing unsupervised learning in hardware. Spiking neural networks more closel... » read more

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