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Media Contacts
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.
ORNL, TVA and TNECD were recognized by the Federal Laboratory Consortium for their impactful partnership that resulted in a record $2.3 billion investment by Ultium Cells, a General Motors and LG Energy Solution joint venture, to build a battery cell manufacturing plant in Spring Hill, Tennessee.
A team led by the ORNL has found a rare quantum material in which electrons move in coordinated ways, essentially “dancing.”
Deborah Frincke, one of the nation’s preeminent computer scientists and cybersecurity experts, serves as associate laboratory director of ORNL’s National Security Science Directorate. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy
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.
On Feb. 18, the world will be watching as NASA’s Perseverance rover makes its final descent into Jezero Crater on the surface of Mars. Mars 2020 is the first NASA mission that uses plutonium-238 produced at the Department of Energy’s Oak Ridge National Laboratory.
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.
An international multi-institution team of scientists has synthesized graphene nanoribbons – ultrathin strips of carbon atoms – on a titanium dioxide surface using an atomically precise method that removes a barrier for custom-designed carbon
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.