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Media Contacts
Laboratory Director Thomas Zacharia presented five Director’s Awards during Saturday night's annual Awards Night event hosted by UT-Battelle, which manages ORNL for the Department of Energy.
Five technologies invented by scientists at the Department of Energy’s Oak Ridge National Laboratory have been selected for targeted investment through ORNL’s Technology Innovation Program.
Larry Allard, a distinguished research staff member at Oak Ridge National Laboratory, has been named a Fellow of the Microanalysis Society.
Oak Ridge National Laboratory’s Innovation Crossroads program welcomes six new science and technology innovators from across the United States to the sixth cohort.
ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.
Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.
ORNL, TVA and TNECD were recognized by the Federal Laboratory Consortium for their impactful partnership that resulted in a record $2.3 billion investment by Ultium Cells, a General Motors and LG Energy Solution joint venture, to build a battery cell manufacturing plant in Spring Hill, Tennessee.
Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.
Momentum Technologies Inc., a Dallas, Texas-based materials science company that is focused on extracting critical metals from electronic waste, has licensed an Oak Ridge National Laboratory process for recovering cobalt and other metals from spent
Researchers at ORNL used quantum optics to advance state-of-the-art microscopy and illuminate a path to detecting material properties with greater sensitivity than is possible with traditional tools.