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Media Contacts
![Lincoln Electric signs agreement with ORNL](/sites/default/files/styles/list_page_thumbnail/public/2019-05/2019-P03122.jpg?h=036a71b7&itok=r3YXr_se)
OAK RIDGE, Tenn., May 8, 2019—Oak Ridge National Laboratory and Lincoln Electric (NASDAQ: LECO) announced their continued collaboration on large-scale, robotic additive manufacturing technology at the Department of Energy’s Advanced Manufacturing InnovationXLab Summit.
![ORNL collaborator Hsiu-Wen Wang led the neutron scattering experiments at the Spallation Neutron Source to probe complex electrolyte solutions that challenge nuclear waste processing at Hanford and other sites. Credit: Genevieve Martin/Oak Ridge National Laboratory, U.S. Dept. of Energy.](/sites/default/files/styles/list_page_thumbnail/public/2019-05/2019-P01240_0.jpg?h=c6980913&itok=RLLi1M-g)
Researchers at the Department of Energy’s Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Washington State University teamed up to investigate the complex dynamics of low-water liquids that challenge nuclear waste processing at federal cleanup sites.
![Virtual universes](/sites/default/files/styles/list_page_thumbnail/public/2019-04/Virtual_universes_0.jpg?h=91594b4a&itok=dhv4iPBH)
Using Summit, the world’s most powerful supercomputer housed at Oak Ridge National Laboratory, a team led by Argonne National Laboratory ran three of the largest cosmological simulations known to date.
![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.
![Small modular reactor computer simulation](/sites/default/files/styles/list_page_thumbnail/public/2019-04/Nuclear_simulation_scale-up.jpg?h=5992a83f&itok=A0oscIPL)
In a step toward advancing small modular nuclear reactor designs, scientists at Oak Ridge National Laboratory have run reactor simulations on ORNL supercomputer Summit with greater-than-expected computational efficiency.
![Scott Smith holding machined aluminum part](/sites/default/files/styles/list_page_thumbnail/public/2019-04/Scott%20SMith%201_0.png?h=250d6eb1&itok=qG5uPX7O)
When Scott Smith looks at a machine tool, he thinks not about what the powerful equipment used to shape metal can do – he’s imagining what it could do with the right added parts and strategies. As ORNL’s leader for a newly formed group, Machining and Machine Tool Research, Smith will have the opportunity to do just that.
![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.
![Microreactors could offer unique mobility and flexibility—opening the possibility for nuclear energy to reach isolated areas.](/sites/default/files/styles/list_page_thumbnail/public/2019-04/Micro%20Reactor%202-03%5B1%5D_0.jpg?h=f3960f67&itok=EVMQYzMt)
Oak Ridge National Laboratory scientists are evaluating paths for licensing remotely operated microreactors, which could provide clean energy sources to hard-to-reach communities, such as isolated areas in Alaska.
![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.