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Media Contacts
An advance in a topological insulator material — whose interior behaves like an electrical insulator but whose surface behaves like a conductor — could revolutionize the fields of next-generation electronics and quantum computing, according to scientists at ORNL.
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.
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.
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 the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2022 R&D 100 Awards, plus special recognition for a battery-related green technology product.
The Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory earned the top ranking today as the world’s fastest on the 59th TOP500 list, with 1.1 exaflops of performance. The system is the first to achieve an unprecedented level of computing performance known as exascale, a threshold of a quintillion calculations per second.
Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
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.