Power/Performance Bits: June 13


Theoretical all-carbon circuits Engineers at the University of Texas at Dallas, the University of Illinois at Urbana-Champaign, the University of Central Florida, and Northwestern University designed a novel computing system made solely from carbon. "The concept brings together an assortment of existing nanoscale technologies and combines them in a new way," said Dr. Joseph S. Friedman, ass... » read more

Manufacturing Bits: May 2


Patterning 1nm features The Center for Functional Nanomaterials (CFN) at the Brookhaven National Laboratory has patterned features down to 1nm using a direct-write lithography technique. Using a scanning transmission electron microscope (STEM), researchers have patterned thin films of the polymer poly(methyl methacrylate), or PMMA, down to 1nm with a spacing between features at 11nm. Re... » read more

Power/Performance Bits: March 28


Storing solar energy as carbon monoxide A team at Indiana University engineered a molecule that collects and stores solar energy without solar panels. The molecule uses light or electricity to convert the greenhouse gas carbon dioxide into carbon monoxide more efficiently than any other method of carbon reduction. Burning fuel such as carbon monoxide produces carbon dioxide and releases e... » read more

System Bits: Feb. 21


Recreating the brain Stanford University and Sandia National Laboratories researchers have created an organic, high-performance, low-energy artificial synapse for neural network computing that aims to better recreate the way the human brain processes information, and could also lead to improvements in brain-machine technologies. Alberto Salleo, associate professor of materials science and e... » read more

Manufacturing Bits: Jan. 31


Fiber-imprint patterning The École polytechnique fédérale de Lausanne (EPFL)--a research institute/university in Lausanne, Switzerland--has put a new twist in nano-imprint patterning technology. It has devised a way to imprint tiny or nano-metric patterns on hollow polymer fiber. Using a technique called thermal drawing, tiny patterns can be printed on both the inside and the outside of ... » read more

Power/Performance Bits: Dec. 6


Perovskites for data storage Scientists at EPFL developed a new perovskite material whose magnetic order can be rapidly changed without disrupting it due to heating that could potentially be used to build next-generation hard drives. "We have essentially discovered the first magnetic photoconductor," said Bálint Náfrádi, a postdoc at EPFL. This new crystal structure combines the advant... » read more

System Bits: Nov. 15


Revolutionizing sports via AI and computer vision A new technology developed by PlayfulVision — an EPFL startup — will be used in all NBA games in the United States starting next year to records all aspects of sporting events for subsequent analysis in augmented reality. Will artificial intelligence and computer vision revolutionize the sports industry? PlayfulVision’s approach uses ... » read more

Power/Performance Bits: Oct. 4


Solar battery Chemists at the University of Wisconsin–Madison and the King Abdullah University of Science and Technology in Saudi Arabia integrated solar cells with a large-capacity battery in a single device that eliminates the usual intermediate step of making electricity and, instead, transfers the energy directly to the battery's electrolyte. The team used a redox flow battery, or R... » read more

Power/Performance Bits: July 19


Atomic storage In the search for ever-smaller storage, a team of scientists at Delft University in the Netherlands built a 1 kilobyte memory where each bit is represented by the position of one single chlorine atom. "In theory, this storage density would allow all books ever created by humans to be written on a single post stamp," said lead scientist Sander Otte. They reached a storage de... » read more

System Bits: June 28


Deep-learning-based virtual reality tool Given that future systems which enable people to interact with virtual environments will require computers to interpret the human hand’s nearly endless variety and complexity of changing motions and joint angles, Purdue University researchers have created a convolutional neural network-based system that is capable of deep learning. [caption id="att... » read more

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