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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.
The U.S. Department of Energy’s Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program is seeking proposals for high-impact, computationally intensive research campaigns in a broad array of science, engineering and computer science domains.
To better understand the spread of SARS-CoV-2, the virus that causes COVID-19, Oak Ridge National Laboratory researchers have harnessed the power of supercomputers to accurately model the spike protein that binds the novel coronavirus to a human cell receptor.
In the quest for advanced vehicles with higher energy efficiency and ultra-low emissions, ORNL researchers are accelerating a research engine that gives scientists and engineers an unprecedented view inside the atomic-level workings of combustion engines in real time.
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.
Scientists from Oak Ridge National Laboratory used high-performance computing to create protein models that helped reveal how the outer membrane is tethered to the cell membrane in certain bacteria.
Kübra Yeter-Aydeniz, a postdoctoral researcher, was recently named the Turkish Women in Science group’s “Scientist of the Week.”
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.
A team led by Dan Jacobson of Oak Ridge National Laboratory used the Summit supercomputer at ORNL to analyze genes from cells in the lung fluid of nine COVID-19 patients compared with 40 control patients.