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Media Contacts
For the second year in a row, a team from the Department of Energy’s Oak Ridge and Los Alamos national laboratories led a demonstration hosted by EPB, a community-based utility and telecommunications company serving Chattanooga, Tennessee.
Researchers at the Department of Energy’s Oak Ridge National Laboratory are refining their design of a 3D-printed nuclear reactor core, scaling up the additive manufacturing process necessary to build it, and developing methods
OAK RIDGE, Tenn., May 5, 2020 — By 2050, the United States will likely be exposed to a larger number of extreme climate events, including more frequent heat waves, longer droughts and more intense floods, which can lead to greater risks for human health, ecosystem stability and regional economies.
OAK RIDGE, Tenn., Feb. 19, 2020 — The U.S. Department of Energy’s Oak Ridge National Laboratory and the Tennessee Valley Authority have signed a memorandum of understanding to evaluate a new generation of flexible, cost-effective advanced nuclear reactors.
The Department of Energy’s Oak Ridge National Laboratory is collaborating with industry on six new projects focused on advancing commercial nuclear energy technologies that offer potential improvements to current nuclear reactors and move new reactor designs closer to deployment.
The United Kingdom’s National Nuclear Laboratory and the U.S. Department of Energy’s Oak Ridge National Laboratory have agreed to cooperate on a wide range of nuclear energy research and development efforts that leverage both organizations’ unique expertise and capabilities.
Scientists at the Department of Energy’s Oak Ridge National Laboratory are the first to successfully simulate an atomic nucleus using a quantum computer. The results, published in Physical Review Letters, demonstrate the ability of quantum systems to compute nuclear ph...
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the