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Media Contacts
When Andrew Sutton arrived at ORNL in late 2020, he knew the move would be significant in more ways than just a change in location.
A force within the supercomputing community, Jack Dongarra developed software packages that became standard in the industry, allowing high-performance computers to become increasingly more powerful in recent decades.
Oak Ridge National Laboratory scientist Amy Elliott is one of 120 women featured in a new exhibit, IfThenSheCan, at the Smithsonian to commemorate Women's History Month. A life-size 3D printed statue of Elliott, a manufacturing scientist, is on display in the Smithsonian Castle in Washington, D.C.
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.
A study led by researchers at ORNL used the nation’s fastest supercomputer to close in on the answer to a central question of modern physics that could help conduct development of the next generation of energy technologies.
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.
Oak Ridge National Laboratory researchers recently used large-scale additive manufacturing with metal to produce a full-strength steel component for a wind turbine, proving the technique as a viable alternative to
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
A novel method to 3D print components for nuclear reactors, developed by the Department of Energy’s Oak Ridge National Laboratory, has been licensed by Ultra Safe Nuclear Corporation.
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.