Polyphase wireless power transfer system achieves 270-kilowatt charge, s...
Mircea Podar, Distinguished Staff Scientist and Leader of the Systems Genetics Group in the Biosciences Division at Oak Ridge National Laboratory, has been elected fellow of the American Academy of Microbiology.
Jitendra Kumar, a researcher at the Department of Energy’s Oak Ridge National Laboratory, has been elevated to the grade of senior member of the Institute of Electrical and Electronics Engineers (IEEE).
Researchers at ORNL demonstrated that sodium-ion batteries can serve as a low-cost, high performance substitute for rechargeable lithium-ion batteries commonly used in robotics, power tools, and grid-scale energy storage.
To better determine the potential energy cost savings among connected homes, researchers at Oak Ridge National Laboratory developed a computer simulation to more accurately compare energy use on similar weather days.
A team of scientists found that critical interactions between microbes and peat moss break down under warming temperatures, impacting moss health and ultimately carbon stored in soil.
Researchers at the Department of Energy’s Oak Ridge National Laboratory have received five 2019 R&D 100 Awards, increasing the lab’s total to 221 since the award’s inception in 1963.
A team including Oak Ridge National Laboratory and University of Tennessee researchers demonstrated a novel 3D printing approach called Z-pinning that can increase the material’s strength and toughness by more than three and a half times compared to conventional additive manufacturing processes.
Oak Ridge National Laboratory is training next-generation cameras called dynamic vision sensors, or DVS, to interpret live information—a capability that has applications in robotics and could improve autonomous vehicle sensing.
A detailed study by Oak Ridge National Laboratory estimated how much more—or less—energy United States residents might consume by 2050 relative to predicted shifts in seasonal weather patterns
Researchers at Oak Ridge National Laboratory are taking inspiration from neural networks to create computers that mimic the human brain—a quickly growing field known as neuromorphic computing.