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.
Three scientists from the Department of Energy’s Oak Ridge National Laboratory have been elected fellows of the American Association for the Advancement of Science, or AAAS.
Oak Ridge National Laboratory scientists recently demonstrated a low-temperature, safe route to purifying molten chloride salts that minimizes their ability to corrode metals. This method could make the salts useful for storing energy generated from the sun’s heat.
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.
More than 50 current employees and recent retirees from ORNL received Department of Energy Secretary’s Honor Awards from Secretary Jennifer Granholm in January as part of project teams spanning the national laboratory system. The annual awards recognized 21 teams and three individuals for service and contributions to DOE’s mission and to the benefit of the nation.
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.
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.
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 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