Polyphase wireless power transfer system achieves 270-kilowatt charge, s...
Brian Post, a researcher in large-scale additive manufacturing at ORNL, has been selected as a recipient of the 2020 Outstanding Young Manufacturing Engineer Award by SME.
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.
ORNL researchers created and tested new wireless charging designs that may double the power density, resulting in a lighter weight system compared with existing technologies.
Researchers demonstrated that an additively manufactured hot stamping die can withstand up to 25,000 usage cycles, proving that this technique is a viable solution for production.
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.
Craig Blue, a program director at the Department of Energy’s Oak Ridge National Laboratory, has been elected a 2019 fellow for SME (formerly known as the Society for Manufacturing Engineers).
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.
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.