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Paul J. Hanson, ORNL Corporate Fellow, has been elected to the 2020 Class of Fellows of the American Geophysical Union.
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.
To better understand how the novel coronavirus behaves and how it can be stopped, scientists have completed a three-dimensional map that reveals the location of every atom in an enzyme molecule critical to SARS-CoV-2 reproduction.
Tony Schmitz, joint faculty researcher in machining and machine tools at Oak Ridge National Laboratory, and mechanical, aerospace and biomedical engineering professor at the University of Tennessee, Knoxville, has been elected to the College of Fellows of the American Society for Precision Engineering.
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
Two staff members at the Department of Energy’s Oak Ridge National Laboratory have received prestigious HENAAC and Luminary Awards from Great Minds in STEM, a nonprofit organization that focuses on promoting STEM careers in underserved
Oak Ridge National Laboratory researchers have designed and additively manufactured a first-of-its-kind aluminum device that enhances the capture of carbon dioxide emitted from fossil fuel plants and other industrial processes.
The Society of Manufacturing Engineers, known as SME, has named William Peter, director of Oak Ridge National Laboratory’s Manufacturing Demonstration Facility in the Energy and Environmental Sciences Directorate, among its 2020 College of SME Fellows.
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.