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The U.S. Department of Energy’s Oak Ridge National Laboratory today unveiled Summit as the world’s most powerful and smartest scientific supercomputer.
Oak Ridge National Laboratory has developed a salt purification lab to study the viability of using liquid salt that contains lithium fluoride and beryllium fluoride, known as FLiBe, to cool molten salt reactors, or MSRs. Multiple American companies developing advanced reactor technol...
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...
Thanks in large part to developing and operating a facility for testing molten salt reactor (MSR) technologies, nuclear experts at the Energy Department’s Oak Ridge National Laboratory (ORNL) are now tackling the next generation of another type of clean energy—concentrating ...
Nuclear physicists are using the nation’s most powerful supercomputer, Titan, at the Oak Ridge Leadership Computing Facility to study particle interactions important to energy production in the Sun and stars and to propel the search for new physics discoveries Direct calculatio...
A new system being developed at Oak Ridge National Laboratory will help builders and home designers select the best construction materials for long-term moisture durability. “It has become challenging to make informed decisions because of modern building code requirements and new ...
At the Department of Energy’s Oak Ridge National Laboratory, Olufemi “Femi” Omitaomu is leveraging Big Data for urban resilience, helping growing cities support future infrastructure and resource needs. A senior research scientist for ORNL’s Computational Sciences and Engineeri...
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