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Three ORNL scientists have been elected fellows of the American Association for the Advancement of Science, or AAAS, the world’s largest general scientific society and publisher of the Science family of journals.
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.
Detecting the activity of CRISPR gene editing tools in organisms with the naked eye and an ultraviolet flashlight is now possible using technology developed at ORNL.
Biologist Larry York’s fascination with plant roots has spurred his research across four continents and inspired him to create accessible tools that enable others to explore the underground world.
ORNL and Tuskegee University have formed a partnership to develop new biodegradable materials for use in buildings, transportation and biomedical applications.
Energy Secretary Jennifer Granholm visited ORNL on Nov. 22 for a two-hour tour, meeting top scientists and engineers as they highlighted projects and world-leading capabilities that address some of the country’s most complex research and technical challenges.
Ten scientists from the Department of Energy’s Oak Ridge National Laboratory are among the world’s most highly cited researchers, according to a bibliometric analysis conducted by the scientific publication analytics firm Clarivate.
Carrie Eckert applies her skills as a synthetic biologist at ORNL to turn microorganisms into tiny factories that produce a variety of valuable fuels, chemicals and materials for the growing bioeconomy.
Having co-developed the power electronics behind ORNL’s compact, high-level wireless power technology for automobiles, Erdem Asa is looking to the skies to apply the same breakthrough to aviation.
Oak Ridge National Laboratory, University of Tennessee and University of Central Florida researchers released a new high-performance computing code designed to more efficiently examine power systems and identify electrical grid disruptions, such as