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Media Contacts
Oak Ridge National Laboratory researchers serendipitously discovered when they automated the beam of an electron microscope to precisely drill holes in the atomically thin lattice of graphene, the drilled holes closed up.
Nine student physicists and engineers from the #1-ranked Nuclear Engineering and Radiological Sciences Program at the University of Michigan, or UM, attended a scintillation detector workshop at Oak Ridge National Laboratory Oct. 10-13.
Global carbon emissions from inland waters such as lakes, rivers, streams and ponds are being undercounted by about 13% and will likely continue to rise given climate events and land use changes, ORNL scientists found.
Researchers at ORNL explored radium’s chemistry to advance cancer treatments using ionizing radiation.
The Department of Defense has recognized UT-Battelle with a 2022 Secretary of Defense Employer Support Freedom Award, the highest recognition given by the United States government to employers for their support of staff members who serve as reserve members of the U.S. Armed Forces, known collectively as the Reserve component.
Larry Allard, a distinguished research staff member at Oak Ridge National Laboratory, has been named a Fellow of the Microanalysis Society.
ORNL Corporate Fellow and Center for Nanophase Materials Sciences researcher Bobby Sumpter has been named fellow of two scientific professional societies: the Institute of Physics and the International Association of Advanced Materials.
Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.
Scientists are using Oak Ridge National Laboratory’s Multicharged Ion Research Facility to simulate the cosmic origin of X-ray emissions resulting when highly charged ions collide with neutral atoms and molecules, such as helium and gaseous hydrogen.
An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.