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Media Contacts
The Spallation Neutron Source at the Department of Energy's Oak Ridge National Laboratory set a world record when its particle accelerator beam operating power reached 1.7 megawatts, substantially improving on the facility’s original design capability.
Scientist-inventors from ORNL will present seven new technologies during the Technology Innovation Showcase on Friday, July 14, from 8 a.m.–4 p.m. at the Joint Institute for Computational Sciences on ORNL’s campus.
Rigoberto Advincula, a renowned scientist at ORNL and professor of Chemical and Biomolecular Engineering at the University of Tennessee, has won the Netzsch North American Thermal Analysis Society Fellows Award for 2023.
Shih-Chieh Kao, manager of the Water Power program at ORNL, has been named a fellow of the American Society of Civil Engineer’s Environmental & Water Resources Institute, or EWRI.
Led by Kelly Chipps of ORNL, scientists working in the lab have produced a signature nuclear reaction that occurs on the surface of a neutron star gobbling mass from a companion star. Their achievement improves understanding of stellar processes generating diverse nuclear isotopes.
Colleen Iversen, ecosystem ecologist, group leader and distinguished staff scientist, has been named director of the Next-Generation Ecosystem Experiments Arctic, or NGEE Arctic, a multi-institutional project studying permafrost thaw and other climate-related processes in Alaska.
Kelly Chipps, a nuclear astrophysicist at ORNL, has been appointed to the Nuclear Science Advisory Committee, or NSAC. The committee provides official advice to DOE and the National Science Foundation, or NSF, about issues relating to the national program for basic nuclear science research.
ORNL’s electromagnetic isotope separator, or EMIS, made history in 2018 when it produced 500 milligrams of the rare isotope ruthenium-96, unavailable anywhere else in the world.
Andrew Lupini, a scientist and inventor at ORNL, has been elected Fellow of the Microscopy Society of America.
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.