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Media Contacts
Wildfires have shaped the environment for millennia, but they are increasing in frequency, range and intensity in response to a hotter climate. The phenomenon is being incorporated into high-resolution simulations of the Earth’s climate by scientists at the Department of Energy’s Oak Ridge National Laboratory, with a mission to better understand and predict environmental change.
Creating energy the way the sun and stars do — through nuclear fusion — is one of the grand challenges facing science and technology. What’s easy for the sun and its billions of relatives turns out to be particularly difficult on Earth.
Scientist-inventors from ORNL will present seven new technologies during the Technology Innovation Showcase on Friday, July 14, from 8 a.m.–4 p.m. at the Joint Institute for Computational Sciences on ORNL’s campus.
ORNL will team up with six of eight companies that are advancing designs and research and development for fusion power plants with the mission to achieve a pilot-scale demonstration of fusion within a decade.
A study led by researchers at ORNL could uncover new ways to produce more powerful, longer-lasting batteries and memory devices.
Led by Kelly Chipps of ORNL, scientists working in the lab have produced a signature nuclear reaction that occurs on the surface of a neutron star gobbling mass from a companion star. Their achievement improves understanding of stellar processes generating diverse nuclear isotopes.
Kelly Chipps, a nuclear astrophysicist at ORNL, has been appointed to the Nuclear Science Advisory Committee, or NSAC. The committee provides official advice to DOE and the National Science Foundation, or NSF, about issues relating to the national program for basic nuclear science research.
A trio of new and improved cosmological simulation codes was unveiled in a series of presentations at the annual April Meeting of the American Physical Society in Minneapolis.
Andrew Lupini, a scientist and inventor at ORNL, has been elected Fellow of the Microscopy Society of America.
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.