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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.
Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS.
The annual Director's Awards recognized four individuals and teams including awards for leadership in quantum simulation development and application on high-performance computing platforms, and revolutionary advancements in the area of microbial
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.
Oak Ridge National Laboratory scientists have discovered a cost-effective way to significantly improve the mechanical performance of common polymer nanocomposite materials.
Five researchers at the Department of Energy’s Oak Ridge National Laboratory have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.
Scientists have tapped the immense power of the Summit supercomputer at Oak Ridge National Laboratory to comb through millions of medical journal articles to identify potential vaccines, drugs and effective measures that could suppress or stop the
An international team of researchers has discovered the hydrogen atoms in a metal hydride material are much more tightly spaced than had been predicted for decades — a feature that could possibly facilitate superconductivity at or near room temperature and pressure.
Scientists at Oak Ridge National Laboratory have conducted a series of breakthrough experimental and computational studies that cast doubt on a 40-year-old theory describing how polymers in plastic materials behave during processing.
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the