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Media Contacts
![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.
![Picture2.png Picture2.png](/sites/default/files/styles/list_page_thumbnail/public/Picture2_1.png?itok=IV4n9XEh)
Oak Ridge National Laboratory scientists studying fuel cells as a potential alternative to internal combustion engines used sophisticated electron microscopy to investigate the benefits of replacing high-cost platinum with a lower cost, carbon-nitrogen-manganese-based catalyst.
Scientists studying a valuable, but vulnerable, species of poplar have identified the genetic mechanism responsible for the species’ inability to resist a pervasive and deadly disease. Their finding, published in the Proceedings of the National Academy of Sciences, could lead to more successful hybrid poplar varieties for increased biofuels and forestry production and protect native trees against infection.
![Ryan Kerekes is leader of the RF, Communications, and Cyber-Physical Security Group at Oak Ridge National Laboratory. Photos by Genevieve Martin, ORNL. Ryan Kerekes is leader of the RF, Communications, and Cyber-Physical Security Group at Oak Ridge National Laboratory. Photos by Genevieve Martin, ORNL.](/sites/default/files/styles/list_page_thumbnail/public/Ryan%20Kerekes%20Profile%20lab1_0.jpg?itok=btnfhbaJ)
As leader of the RF, Communications, and Cyber-Physical Security Group at Oak Ridge National Laboratory, Kerekes heads an accelerated lab-directed research program to build virtual models of critical infrastructure systems like the power grid that can be used to develop ways to detect and repel cyber-intrusion and to make the network resilient when disruption occurs.
![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.
![Oak Ridge National Laboratory researcher Halil Tekinalp combines silanes and polylactic acid to create supertough renewable plastic. Oak Ridge National Laboratory researcher Halil Tekinalp combines silanes and polylactic acid to create supertough renewable plastic.](/sites/default/files/styles/list_page_thumbnail/public/news/images/02%20Materials-Supertough_bioplastic.jpg?itok=64jAyN8y)
A novel method developed at Oak Ridge National Laboratory creates supertough renewable plastic with improved manufacturability. Working with polylactic acid, a biobased plastic often used in packaging, textiles, biomedical implants and 3D printing, the research team added tiny amo...
![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