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Media Contacts
![Edmon Begoli](/sites/default/files/styles/list_page_thumbnail/public/2019-08/2017-P04474.png?h=4b95bb49&itok=1YkLx9Jz)
Artificial intelligence (AI) techniques have the potential to support medical decision-making, from diagnosing diseases to prescribing treatments. But to prioritize patient safety, researchers and practitioners must first ensure such methods are accurate.
![International Conference on Neuromorphic Systems (ICONS)](/sites/default/files/styles/list_page_thumbnail/public/2019-08/logo_no_text.png?h=2c1ce78b&itok=xm-saFEM)
Materials scientists, electrical engineers, computer scientists, and other members of the neuromorphic computing community from industry, academia, and government agencies gathered in downtown Knoxville July 23–25 to talk about what comes next in
![Galactic wind simulation](/sites/default/files/styles/list_page_thumbnail/public/2019-07/Robertson%5B2%5D.png?h=319b3f54&itok=jK6lUXEt)
Using the Titan supercomputer at Oak Ridge National Laboratory, a team of astrophysicists created a set of galactic wind simulations of the highest resolution ever performed. The simulations will allow researchers to gather and interpret more accurate, detailed data that elucidates how galactic winds affect the formation and evolution of galaxies.
![Molecular dynamics simulations of the Fs-peptide revealed the presence of at least eight distinct intermediate stages during the process of protein folding. The image depicts a fully folded helix (1), various transitional forms (2–8), and one misfolded state (9). By studying these protein folding pathways, scientists hope to identify underlying factors that affect human health.](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Slide1_0.png?h=c855054e&itok=aNbgxXsc)
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.
![ORNL-led collaboration solves a beta-decay puzzle with advanced nuclear models](/sites/default/files/styles/list_page_thumbnail/public/2019-03/decay_coverSize_4%5B21%5D_0.jpg?h=843037ec&itok=BU6x1GD8)
OAK RIDGE, Tenn., March 11, 2019—An international collaboration including scientists at the Department of Energy’s Oak Ridge National Laboratory solved a 50-year-old puzzle that explains why beta decays of atomic nuclei
![(From left) ORNL Associate Laboratory Director for Computing and Computational Sciences Jeff Nichols; ORNL Health Data Sciences Institute Director Gina Tourassi; DOE Deputy Under Secretary for Science Thomas Cubbage; ORNL Task Lead for Biostatistics Blair Christian; and ORNL Research Scientist Ioana Danciu were invited to the White House to showcase an ORNL-developed digital tool aimed at better matching cancer patients with clinical trials.](/sites/default/files/styles/list_page_thumbnail/public/2019-03/TourassiWH%5B1%5D.png?h=26b5064d&itok=HUC2iYmE)
OAK RIDGE, Tenn., March 4, 2019—A team of researchers from the Department of Energy’s Oak Ridge National Laboratory Health Data Sciences Institute have harnessed the power of artificial intelligence to better match cancer patients with clinical trials.
OAK RIDGE, Tenn., Feb. 12, 2019—A team of researchers from the Department of Energy’s Oak Ridge and Los Alamos National Laboratories has partnered with EPB, a Chattanooga utility and telecommunications company, to demonstrate the effectiveness of metro-scale quantum key distribution (QKD).
![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