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Media Contacts
ORNL's Larry Baylor and Andrew Lupini have been elected fellows of the American Physical Society.
A research team at Oak Ridge National Laboratory have 3D printed a thermal protection shield, or TPS, for a capsule that will launch with the Cygnus cargo spacecraft as part of the supply mission to the International Space Station.
Researchers working with Oak Ridge National Laboratory developed a new method to observe how proteins, at the single-molecule level, bind with other molecules and more accurately pinpoint certain molecular behavior in complex
ASM International recently elected three researchers from ORNL as 2021 fellows. Selected were Beth Armstrong and Govindarajan Muralidharan, both from ORNL’s Material Sciences and Technology Division, and Andrew Payzant from the Neutron Scattering Division.
Scientists at ORNL and the University of Tennessee, Knoxville, have found a way to simultaneously increase the strength and ductility of an alloy by introducing tiny precipitates into its matrix and tuning their size and spacing.
Researchers from NASA’s Jet Propulsion Laboratory and Oak Ridge National Laboratory successfully created amorphous ice, similar to ice in interstellar space and on icy worlds in our solar system. They documented that its disordered atomic behavior is unlike any ice on Earth.
The Department of Energy’s Office of Science has selected five Oak Ridge National Laboratory scientists for Early Career Research Program awards.
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.
Oak Ridge National Laboratory researchers, in collaboration with Cincinnati Inc., demonstrated the potential for using multimaterials and recycled composites in large-scale applications by 3D printing a mold that replicated a single facet of a
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.