Polyphase wireless power transfer system achieves 270-kilowatt charge, s...
Researchers at Oak Ridge National Laboratory developed self-healing elastomers that demonstrated unprecedented adhesion strength and the ability to adhere to many surfaces, which could broaden their potential use
Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences contributed to a groundbreaking experiment published in Science that tracks the real-time transport of individual molecules.
Scientists at Oak Ridge National Laboratory and the University of Tennessee designed and demonstrated a method to make carbon-based materials that can be used as electrodes compatible with a specific semiconductor circuitry.
Four research teams from the Department of Energy’s Oak Ridge National Laboratory and their technologies have received 2020 R&D 100 Awards.
A team led by Oak Ridge National Laboratory developed a novel, integrated approach to track energy-transporting ions within an ultra-thin material, which could unlock its energy storage potential leading toward faster charging, longer-lasting devices.
Three researchers at Oak Ridge National Laboratory will lead or participate in collaborative research projects aimed at harnessing the power of quantum mechanics to advance a range of technologies including computing, fiber optics and network
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.
Using additive manufacturing, scientists experimenting with tungsten at Oak Ridge National Laboratory hope to unlock new potential of the high-performance heat-transferring material used to protect components from the plasma inside a fusion reactor. Fusion requires hydrogen isotopes to reach millions of degrees.
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 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