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Media Contacts
![An X-ray CT image of a 3D-printed metal turbine blade was reconstructed using ORNL’s neural network and advanced algorithms. Credit: Amir Ziabari/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-01/Manufacturing%20-%20Defect%20detection%202_0.jpg?h=259e5a75&itok=CwpLQv6U)
Algorithms developed at Oak Ridge National Laboratory can greatly enhance X-ray computed tomography images of 3D-printed metal parts, resulting in more accurate, faster scans.
![Distinguished Inventors](/sites/default/files/styles/list_page_thumbnail/public/2020-12/inventors.jpg?h=4631f1c1&itok=xhAGY0kv)
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.
![Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-11/AAASfellows.jpg?h=d761c044&itok=opKRkA17)
Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS.
![Paul Kent, shown above posing with Summit in April 2018, received the 2020 ORNL Director’s Award for Outstanding Individual Accomplishment in Science and Technology. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-11/DA_Kent.jpg?h=48cf6540&itok=Ocw9WcgV)
The annual Director's Awards recognized four individuals and teams including awards for leadership in quantum simulation development and application on high-performance computing platforms, and revolutionary advancements in the area of microbial
![These fuel assembly brackets, manufactured by ORNL in partnership with Framatome and Tennessee Valley Authority, are the first 3D-printed safety-related components to be inserted into a nuclear power plant. Credit: Fred List/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-10/FramatomeCB1.jpg?h=7c790887&itok=oVGkqZYZ)
The Transformational Challenge Reactor, or TCR, a microreactor built using 3D printing and other new advanced technologies, could be operational by 2024.
![Researcher Chase Joslin uses Peregrine software to monitor and analyze a component being 3D printed at the Manufacturing Demonstration Facility at ORNL. Credit: Luke Scime/ORNL, U.S. Dept. of Energy.](/sites/default/files/styles/list_page_thumbnail/public/2020-08/Peregrine%20Chase%20Joslin_0.jpg?h=51c7b451&itok=4Hc6PNwu)
Oak Ridge National Laboratory researchers have developed artificial intelligence software for powder bed 3D printers that assesses the quality of parts in real time, without the need for expensive characterization equipment.
![SPRUCE experiment](/sites/default/files/styles/list_page_thumbnail/public/2020-08/SPRUCE_0.png?h=9afda364&itok=zCibJUsI)
Oak Ridge National Laboratory scientists evaluating northern peatland responses to environmental change recorded extraordinary fine-root growth with increasing temperatures, indicating that this previously hidden belowground mechanism may play an important role in how carbon-rich peatlands respond to warming.
![Drone shot above SPRUCE enclosure](/sites/default/files/styles/list_page_thumbnail/public/2020-07/P20_Drone_YUN00190_0.jpg?h=fe23bcc2&itok=PwOXZq1F)
Scientists at Oak Ridge National Laboratory have demonstrated a direct relationship between climate warming and carbon loss in a peatland ecosystem.
![Sergei Kalinin](/sites/default/files/styles/list_page_thumbnail/public/2020-07/2019-P00126_0.png?h=5969a3b5&itok=66cucDCt)
Five researchers at the Department of Energy’s Oak Ridge National Laboratory have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.
![Map with focus on sub-saharan Africa](/sites/default/files/styles/list_page_thumbnail/public/2020-07/firms3-Africa-NASA_0.jpg?h=27f1d52b&itok=G8uUS5cH)
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.