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Power/Performance Bits: July 27


Amplifying light for lidar Engineers at University of Texas at Austin and University of Virginia developed a light detector that can amplify weak light signals and reduce noise to improve the accuracy of lidar. "Autonomous vehicles send out laser signals that bounce off objects to tell you how far away you are. Not much light comes back, so if your detector is putting out more noise than th... » read more

Power/Performance Bits: May 19


Neuromorphic magnetic nanowires Researchers from the University of Texas at Austin, University of Texas at Dallas, and Sandia National Laboratory propose a neuromorphic computing method using magnetic components. The team says this approach can cut the energy cost of training neural networks. "Right now, the methods for training your neural networks are very energy-intensive," said Jean Ann... » read more

Power/Performance Bits: June 19


Tandem solar reaches 25.2% efficiency In the push for ever-more efficient solar panels, researchers are turning to tandem, or double-junction, photovoltaics. Tandem solar panels use two different types of solar cell capable of absorbing different wavelengths of light stacked on top of each other to maximize the conversion of light rays into electrical power. Recently, two groups have reache... » read more

Power/Performance Bits: Nov. 23


Increasing lithium battery density Researchers at Columbia University developed a new method to increase the energy density of lithium batteries using a trilayer structure that is stable in ambient air. "When lithium batteries are charged the first time, they lose anywhere from 5-20% energy in that first cycle," said Yuan Yang, assistant professor of materials science and engineering at C... » read more