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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.
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.
The Spallation Neutron Source at the Department of Energy’s Oak Ridge National Laboratory has broken a new record by ending its first neutron production cycle in fiscal year 2019 at its design power level of 1.4 megawatts.
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 studying a valuable, but vulnerable, species of poplar have identified the genetic mechanism responsible for the species’ inability to resist a pervasive and deadly disease. Their finding, published in the Proceedings of the National Academy of Sciences, could lead to more successful hybrid poplar varieties for increased biofuels and forestry production and protect native trees against infection.
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.
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 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