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Media Contacts
Kathy McCarthy, associate laboratory director for Fusion and Fission Energy and Science at the Department of Energy’s Oak Ridge National Laboratory, has been elected fellow of the American Nuclear Society for her nationally and internationally recognized leadership in nuclear energy and fusion.
The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.
Thirty-two Oak Ridge National Laboratory employees were named among teams recognized by former DOE Secretary Dan Brouillette with Secretary’s Honor Awards as he completed his term. Four teams received new awards that reflect DOE responses to the coronavirus pandemic.
Brian Damiano, head of the Centrifuge Engineering and Fabrication Section, has been elected fellow of the American Society of Mechanical Engineers.
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.
David Kropaczek, director of the Consortium for Advanced Simulation of Light Water Reactors, or CASL, at the Department of Energy’s Oak Ridge National Laboratory, has been named a fellow of the American Nuclear Society.
ORNL has added 10 virtual tours to its campus map, each with multiple views to show floor plans, rotating dollhouse views and 360-degree navigation. As a user travels through a map, pop-out informational windows deliver facts, videos, graphics and links to other related content.
Four research teams from the Department of Energy’s Oak Ridge National Laboratory and their technologies have received 2020 R&D 100 Awards.
ORNL and Department of Energy officials dedicated the launch of two clean energy research initiatives that focus on the recycling and recovery of advanced manufacturing materials and on connected and
Oak Ridge National Laboratory researchers have developed artificial intelligence software for powder bed 3D printers that assesses the quality of parts in real time, without the need for expensive characterization equipment.