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Media Contacts
A team of scientists has for the first time measured the elusive weak interaction between protons and neutrons in the nucleus of an atom. They had chosen the simplest nucleus consisting of one neutron and one proton for the study.
Three researchers from the Department of Energy’s Oak Ridge National Laboratory have been elected fellows of the American Physical Society (APS). Fellows of the APS are recognized for their exceptional contributions to the physics enterprise in outstanding resear...
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 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 ...
Qrypt, Inc., has exclusively licensed a novel cyber security technology from the Department of Energy’s Oak Ridge National Laboratory, promising a stronger defense against cyberattacks including those posed by quantum computing.
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 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