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![MDF New Hires](/sites/default/files/styles/list_page_thumbnail/public/MDF%20New%20Hires.png?itok=252gnkPR)
Two leaders in US manufacturing innovation, Thomas Kurfess and Scott Smith, are joining the Department of Energy’s Oak Ridge National Laboratory to support its pioneering research in advanced manufacturing.
![The sensors measure parameters like temperature, chemicals and electric grid elements for industrial and electrical applications. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy The sensors measure parameters like temperature, chemicals and electric grid elements for industrial and electrical applications. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/drone%20inspecting%20EPB%20pole%20mounted%20transformers.jpg?itok=CiRIK4cC)
Brixon, Inc., has exclusively licensed a multiparameter sensor technology from the Department of Energy’s Oak Ridge National Laboratory. The integrated platform uses various sensors that measure physical and environmental parameters and respond to standard security applications.
![Graphical representation of a deuteron, the bound state of a proton (red) and a neutron (blue). Credit: Andy Sproles/Oak Ridge National Laboratory, U.S. Dept. of Energy. Graphical representation of a deuteron, the bound state of a proton (red) and a neutron (blue). Credit: Andy Sproles/Oak Ridge National Laboratory, U.S. Dept. of Energy.](/sites/default/files/styles/list_page_thumbnail/public/news/images/deuteron%5B4%5D.jpg?itok=hEV9C82i)
Scientists at the Department of Energy’s Oak Ridge National Laboratory are the first to successfully simulate an atomic nucleus using a quantum computer. The results, published in Physical Review Letters, demonstrate the ability of quantum systems to compute nuclear ph...
![ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system. ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.](/sites/default/files/styles/list_page_thumbnail/public/news/images/RAvENNA%20release%20pic.png?itok=2bDpK5Mo)
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