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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.
Oak Ridge National Laboratory, University of Tennessee and University of Central Florida researchers released a new high-performance computing code designed to more efficiently examine power systems and identify electrical grid disruptions, such as
Oak Ridge National Laboratory researchers developed and demonstrated algorithm-based controls for a hybrid electric bus that yielded up to 30% energy savings compared with existing controls.
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.
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
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 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