Updated software improves slicing for large-format 3D printing
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.
Oak Ridge National Laboratory physicist Elizabeth “Libby” Johnson (1921-1996), one of the world’s first nuclear reactor operators, standardized the field of criticality safety with peers from ORNL and Los Alamos National Laboratory.
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.
As climate change leads to larger and more frequent wildfires, researchers at ORNL are using sensors, drones and machine learning to both prevent fires and reduce their damage to the electric grid.
Though Nell Barber wasn’t sure what her future held after graduating with a bachelor’s degree in psychology, she now uses her interest in human behavior to design systems that leverage machine learning algorithms to identify faces in a crowd.
To solve a long-standing puzzle about how long a neutron can “live” outside an atomic nucleus, physicists entertained a wild but testable theory positing the existence of a right-handed version of our left-handed universe.
ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.
How an Alvin M. Weinberg Fellow is increasing security for critical infrastructure components
ORNL and the Tennessee Valley Authority, or TVA, are joining forces to advance decarbonization technologies from discovery through deployment through a new memorandum of understanding, or MOU.
A study led by researchers at ORNL used the nation’s fastest supercomputer to close in on the answer to a central question of modern physics that could help conduct development of the next generation of energy technologies.