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Media Contacts
![ORNL staff members (from left) Ashley Shields, Michael Galloway, Ketan Maheshwari and Andrew Miskowiec are collaborating on a project focused on predicting and analyzing crystal structures of new uranium oxide phases. Credit: Jason Richards/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2019-03/teamphotoforhighlight_0.jpg?h=a00326b7&itok=O4yDtVj6)
Scientists at the Department of Energy’s Oak Ridge National Laboratory are working to understand both the complex nature of uranium and the various oxide forms it can take during processing steps that might occur throughout the nuclear fuel cycle.
![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.
![In ORNL’s Low Activation Materials Development and Analysis Laboratory, Field makes use of a transmission electron microscope to examine a sample made with a focused ion beam. He investigates the defects produced in a FeCrAl alloy bombarded with neutrons in HFIR. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2019-03/2018-P08721%20%28first%29.jpg?h=8f9cfe54&itok=sRzTcetb)
Kevin Field at the Department of Energy’s Oak Ridge National Laboratory synthesizes and scrutinizes materials for nuclear power systems that must perform safely and efficiently over decades of irradiation.
![ORNL nuclear engineer Chris Petrie](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Nuclear-Follow_your_senses_ORNL_2.jpg?h=7d719b4a&itok=xTiBlfq8)
Oak Ridge National Laboratory is using ultrasonic additive manufacturing to embed highly accurate fiber optic sensors in heat- and radiation-resistant materials, allowing for real-time monitoring that could lead to greater insights and safer reactors.
![(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.
![As part of a preliminary study, ORNL scientists used critical location data collected from Twitter to map the location of certain power outages across the United States.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/PowerOutageTweets_map_0.png?h=6448fdc1&itok=AUit-O2Y)
Gleaning valuable data from social platforms such as Twitter—particularly to map out critical location information during emergencies— has become more effective and efficient thanks to Oak Ridge National Laboratory.
![An ORNL-developed graphite foam, which could be used in plasma-facing components in fusion reactors, performed well during testing at the Wendlestein 7-X stellarator in Germany.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/W7-XPlasmaExposure_0.jpg?h=d5d04e3b&itok=uKiauhdF)
Scientists have tested a novel heat-shielding graphite foam, originally created at Oak Ridge National Laboratory, at Germany’s Wendelstein 7-X stellarator with promising results for use in plasma-facing components of fusion reactors.
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).
![ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La](/sites/default/files/styles/list_page_thumbnail/public/study_area_one_dest_2.jpg?itok=2cWFkQvW)
Oak Ridge National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.
![Symposium attendees represented ORNL, the University of Arizona, Georgia Tech, the University of Tennessee-Knoxville, and Brigham Young University. Symposium attendees represented ORNL, the University of Arizona, Georgia Tech, the University of Tennessee-Knoxville, and Brigham Young University.](/sites/default/files/styles/list_page_thumbnail/public/news/images/2019-P00148%5B2%5D%20r1.jpg?itok=imqhuQWL)
Quantum experts from across government and academia descended on Oak Ridge National Laboratory on Wednesday, January 16 for the lab’s first-ever Quantum Networking Symposium. The symposium’s purpose, said organizer and ORNL senior scientist Nick Peters, was to gather quantum an...