Polyphase wireless power transfer system achieves 270-kilowatt charge, s...
To minimize potential damage from underground oil and gas leaks, Oak Ridge National Laboratory is co-developing a quantum sensing system to detect pipeline leaks more quickly.
Researchers at Oak Ridge National Laboratory were part of an international team that collected a treasure trove of data measuring precipitation, air particles, cloud patterns and the exchange of energy between the atmosphere and the sea ice.
Oak Ridge National Laboratory researchers have developed a thin film, highly conductive solid-state electrolyte made of a polymer and ceramic-based composite for lithium metal batteries.
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.
In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly.
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.
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.
A team of researchers at Oak Ridge National Laboratory have demonstrated that designed synthetic polymers can serve as a high-performance binding material for next-generation lithium-ion batteries.
A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool