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![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.
![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.
![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.
![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.
![Alex Roschli in front of BAAM](/sites/default/files/styles/list_page_thumbnail/public/2019-03/2018-p09585.jpg?h=af53702d&itok=YVD6zmU4)
Alex Roschli is no stranger to finding himself in unique situations. After all, the early career researcher in ORNL’s Manufacturing Systems Research group bears a last name that only 29 other people share in the United States, and he’s certain he’s the only Roschli (a moniker that hails from Switzerland) with the first name Alex.
![The concrete parts are installed in a residential and commercial tower (above center and below) on the site of the Domino Sugar Factory along the waterfront in Brooklyn. Windows in the tower resemble sugar crystals. Image credit: Gate Precast](/sites/default/files/styles/list_page_thumbnail/public/2019-03/392_4.jpg?h=2e111cc1&itok=PaciKdQX)
A residential and commercial tower under development in Brooklyn that is changing the New York City skyline has its roots in research at the Department of Energy’s Oak Ridge National Laboratory.
![ORNL-led collaboration solves a beta-decay puzzle with advanced nuclear models](/sites/default/files/styles/list_page_thumbnail/public/2019-03/decay_coverSize_4%5B21%5D_0.jpg?h=843037ec&itok=BU6x1GD8)
OAK RIDGE, Tenn., March 11, 2019—An international collaboration including scientists at the Department of Energy’s Oak Ridge National Laboratory solved a 50-year-old puzzle that explains why beta decays of atomic nuclei
![Transportation Energy Data Book Edition 37](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Transportation-Logging_the_miles_ORNL_0.jpg?h=ade3edc7&itok=wGiEijHl)
Oak Ridge National Laboratory’s latest Transportation Energy Data Book: Edition 37 reports that the number of vehicles nationwide is growing faster than the population, with sales more than 17 million since 2015, and the average household vehicle travels more than 11,000 miles per year.
![(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.