Katy Bradford: Cassette approach offers compelling construction solution
The U.S. Department of Energy’s Office of Science announced allocations of supercomputer access to 51 high-impact computational science projects for 2022 through its Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program.
ORNL's Larry Baylor and Andrew Lupini have been elected fellows of the American Physical Society.
Sergei Kalinin, a scientist and inventor at the Department of Energy’s Oak Ridge National Laboratory, has been elected a fellow of the Microscopy Society of America professional society.
The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.
The U.S. Department of Energy’s Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program is seeking proposals for high-impact, computationally intensive research campaigns in a broad array of science, engineering and computer science domains.
Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.
Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS.
Momentum Technologies Inc., a Dallas, Texas-based materials science company that is focused on extracting critical metals from electronic waste, has licensed an Oak Ridge National Laboratory process for recovering cobalt and other metals from spent
The combination of bioenergy with carbon capture and storage could cost-effectively sequester hundreds of millions of metric tons per year of carbon dioxide in the United States, making it a competitive solution for carbon management, according to a new analysis by ORNL scientists.
Researchers at ORNL used quantum optics to advance state-of-the-art microscopy and illuminate a path to detecting material properties with greater sensitivity than is possible with traditional tools.