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Media Contacts
![ORNL researchers printed thin metal walls using large-scale metal additive manufacturing, a wire-arc process that demonstrated stability, uniformity and precise geometry throughout the deposition. The method could be a viable option for large-scale additive manufacturing of metal components. ORNL collaborated with industry partner Lincoln Electric. Credit: Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2019-04/Metal_print_1_0.png?h=def6dc7e&itok=0uzrZAMc)
A novel additive manufacturing method developed by researchers at Oak Ridge National Laboratory could be a promising alternative for low-cost, high-quality production of large-scale metal parts with less material waste.
![Using artificial intelligence, Oak Ridge National Laboratory analyzed data from published medical studies to reveal the potential of direct and indirect impacts of bullying.](/sites/default/files/styles/list_page_thumbnail/public/2019-04/bullying_img.png?h=48484608&itok=zxX54Jz1)
Oak Ridge National Laboratory is using artificial intelligence to analyze data from published medical studies associated with bullying to reveal the potential of broader impacts, such as mental illness or disease.
![Low-cost, compact, printed sensor that can collect and transmit data on electrical appliances for better load monitoring](/sites/default/files/styles/list_page_thumbnail/public/2019-03/2019-P01301_0.jpg?h=c6980913&itok=y0S4bq0p)
Scientists at Oak Ridge National Laboratory have developed a low-cost, printed, flexible sensor that can wrap around power cables to precisely monitor electrical loads from household appliances to support grid operations.
![(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.
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.
![Nuclear—Deep space travel Nuclear—Deep space travel](/sites/default/files/styles/list_page_thumbnail/public/Screen%20Shot%202018-12-19%20at%2010.29.32%20AM.png?itok=hq0dlVIf)
By automating the production of neptunium oxide-aluminum pellets, Oak Ridge National Laboratory scientists have eliminated a key bottleneck when producing plutonium-238 used by NASA to fuel deep space exploration.
![18-G01703 PinchPoint-v2.jpg 18-G01703 PinchPoint-v2.jpg](/sites/default/files/styles/list_page_thumbnail/public/18-G01703%20PinchPoint-v2.jpg?itok=paJUPDI1)
Researchers used neutron scattering at Oak Ridge National Laboratory’s Spallation Neutron Source to investigate bizarre magnetic behavior, believed to be a possible quantum spin liquid rarely found in a three-dimensional material. QSLs are exotic states of matter where magnetism continues to fluctuate at low temperatures instead of “freezing” into aligned north and south poles as with traditional magnets.
![Using as much as 50 percent lignin by weight, a new composite material created at ORNL is well suited for use in 3D printing. Using as much as 50 percent lignin by weight, a new composite material created at ORNL is well suited for use in 3D printing.](/sites/default/files/styles/list_page_thumbnail/public/2018-P09551.jpg?itok=q7Ri01Qb)
Scientists at the Department of Energy’s Oak Ridge National Laboratory have created a recipe for a renewable 3D printing feedstock that could spur a profitable new use for an intractable biorefinery byproduct: lignin.