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.
A rare isotope in high demand for treating cancer is now more available to pharmaceutical companies developing and testing new drugs.
Balendra Sutharshan, deputy associate laboratory director for operational systems at DOE’s Pacific Northwest National Laboratory, has joined ORNL as associate laboratory director for the Isotope Science and Engineering Directorate.
Brian Damiano, head of the Centrifuge Engineering and Fabrication Section, has been elected fellow of the American Society of Mechanical Engineers.
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.
Porter Bailey started and will end his 33-year career at ORNL in the same building: 7920 of the Radiochemical Engineering Development Center.
The combination of bioenergy with carbon capture and storage could cost-effectively sequester hundreds of millions of metric tons per year of carbon dioxide in the United States, making it a competitive solution for carbon management, according to a new analysis by ORNL scientists.
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.