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For years, Duane Starr led workshops at ORNL to help others from across the U.S. government understand uranium processing technologies. After his retirement, Starr donated a 5-foot-tall working model, built in his garage, that demonstrates vibration harmonics, consistent with operation of a super critical gas centrifuge rotor, a valuable resource to ongoing ORNL-led workshops.
Scientists at ORNL used their knowledge of complex ecosystem processes, energy systems, human dynamics, computational science and Earth-scale modeling to inform the nation’s latest National Climate Assessment, which draws attention to vulnerabilities and resilience opportunities in every region of the country.
A type of peat moss has surprised scientists with its climate resilience: Sphagnum divinum is actively speciating in response to hot, dry conditions.
The Autonomous Systems group at ORNL is in high demand as it incorporates remote sensing into projects needing a bird’s-eye perspective.
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.
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.
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.
Improved data, models and analyses from ORNL scientists and many other researchers in the latest global climate assessment report provide new levels of certainty about what the future holds for the planet