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Media Contacts
In response to a renewed international interest in molten salt reactors, researchers from the Department of Energy’s Oak Ridge National Laboratory have developed a novel technique to visualize molten salt intrusion in graphite.
A type of peat moss has surprised scientists with its climate resilience: Sphagnum divinum is actively speciating in response to hot, dry conditions.
A series of new classes at Pellissippi State Community College will offer students a new career path — and a national laboratory a pipeline of workers who have the skills needed for its own rapidly growing programs.
Three scientists from the Department of Energy’s Oak Ridge National Laboratory have been elected fellows of the American Association for the Advancement of Science, or AAAS.
As part of a multi-institutional research project, scientists at ORNL leveraged their computational systems biology expertise and the largest, most diverse set of health data to date to explore the genetic basis of varicose veins.
A new paper published in Nature Communications adds further evidence to the bradykinin storm theory of COVID-19’s viral pathogenesis — a theory that was posited two years ago by a team of researchers at the Department of Energy’s Oak Ridge National Laboratory.
Researchers at ORNL explored radium’s chemistry to advance cancer treatments using ionizing radiation.
Two decades in the making, a new flagship facility for nuclear physics opened on May 2, and scientists from the Department of Energy’s Oak Ridge National Laboratory have a hand in 10 of its first 34 experiments.
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 of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.