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Media Contacts
OAK RIDGE, Tenn., Feb. 12, 2019—A team of researchers from the Department of Energy’s Oak Ridge and Los Alamos National Laboratories has partnered with EPB, a Chattanooga utility and telecommunications company, to demonstrate the effectiveness of metro-scale quantum key distribution (QKD).
OAK RIDGE, Tenn., Feb. 8, 2019—The Department of Energy’s Oak Ridge National Laboratory has named Sean Hearne director of the Center for Nanophase Materials Sciences. The center is a DOE Office of Science User Facility that brings world-leading resources and capabilities to the nanoscience resear...
OAK RIDGE, Tenn., Jan. 31, 2019—A new electron microscopy technique that detects the subtle changes in the weight of proteins at the nanoscale—while keeping the sample intact—could open a new pathway for deeper, more comprehensive studies of the basic building blocks of life.
Scientists at the Department of Energy’s Oak Ridge National Laboratory used neutrons, isotopes and simulations to “see” the atomic structure of a saturated solution and found evidence supporting one of two competing hypotheses about how ions come
Scientists at the Department of Energy’s Oak Ridge National Laboratory induced a two-dimensional material to cannibalize itself for atomic “building blocks” from which stable structures formed. The findings, reported in Nature Communications, provide insights that ...
The Department of Energy’s Oak Ridge National Laboratory is now producing actinium-227 (Ac-227) to meet projected demand for a highly effective cancer drug through a 10-year contract between the U.S. DOE Isotope Program and Bayer.
A scientific team led by the Department of Energy’s Oak Ridge National Laboratory has found a new way to take the local temperature of a material from an area about a billionth of a meter wide, or approximately 100,000 times thinner than a human hair. This discove...
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