Polyphase wireless power transfer system achieves 270-kilowatt charge, s...
OAK RIDGE, Tenn., Feb. 12, 2020 -- Michael Brady, a researcher at the Department of Energy’s Oak Ridge National Laboratory, has been named fellow of the National Association of Corrosion Engineers, or NACE International.
The prospect of simulating a fusion plasma is a step closer to reality thanks to a new computational tool developed by scientists in fusion physics, computer science and mathematics at ORNL.
Rigoberto “Gobet” Advincula has been named Governor’s Chair of Advanced and Nanostructured Materials at Oak Ridge National Laboratory and the University of Tennessee.
Researchers at Oak Ridge National Laboratory demonstrated that an additively manufactured polymer layer, when applied to carbon fiber reinforced plastic, or CFRP, can serve as an effective protector against aircraft lightning strikes.
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.
Researchers at Oak Ridge National Laboratory proved that a certain class of ionic liquids, when mixed with commercially available oils, can make gears run more efficiently with less noise and better durability.
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.