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Media Contacts
Simulations performed on the Summit supercomputer at ORNL revealed new insights into the role of turbulence in mixing fluids and could open new possibilities for projecting climate change and studying fluid dynamics.
For the third year in a row, the Quantum Science Center held its signature workforce development event: a comprehensive summer school for students and early-career scientists designed to facilitate conversations and hands-on activities related to
A study led by researchers at ORNL could uncover new ways to produce more powerful, longer-lasting batteries and memory devices.
A team of researchers from ORNL was recognized by the National Cancer Institute in March for their unique contributions in the fight against cancer.
Oak Ridge National Laboratory, in partnership with the National Oceanic and Atmospheric Administration, is launching a new supercomputer dedicated to climate science research. The new system is the fifth supercomputer to be installed and run by the National Climate-Computing Research Center at ORNL.
ORNL researchers are deploying their broad expertise in climate data and modeling to create science-based mitigation strategies for cities stressed by climate change as part of two U.S. Department of Energy Urban Integrated Field Laboratory projects.
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.
Five National Quantum Information Science Research Centers are leveraging the behavior of nature at the smallest scales to develop technologies for science’s most complex problems.
Travis Humble has been named director of the Quantum Science Center headquartered at ORNL. The QSC is a multi-institutional partnership that spans industry, academia and government institutions and is tasked with uncovering the full potential of quantum materials, sensors and algorithms.
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.