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Media Contacts
ORNL is home to the world's fastest exascale supercomputer, Frontier, which was built in part to facilitate energy-efficient and scalable AI-based algorithms and simulations.
Anne Campbell, an R&D associate in ORNL’s Materials Science and Technology Division since 2016, has been selected as an associate editor of the Journal of Nuclear Materials.
Researchers at the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2022 R&D 100 Awards, plus special recognition for a battery-related green technology product.
A force within the supercomputing community, Jack Dongarra developed software packages that became standard in the industry, allowing high-performance computers to become increasingly more powerful in recent decades.
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.
Using complementary computing calculations and neutron scattering techniques, researchers from the Department of Energy’s Oak Ridge and Lawrence Berkeley national laboratories and the University of California, Berkeley, discovered the existence of an elusive type of spin dynamics in a quantum mechanical system.
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.
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.