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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.
OAK RIDGE, Tenn., May 7, 2019—The U.S. Department of Energy today announced a contract with Cray Inc. to build the Frontier supercomputer at Oak Ridge National Laboratory, which is anticipated to debut in 2021 as the world’s most powerful computer with a performance of greater than 1.5 exaflops.
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.
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.
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.
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.
Ionic conduction involves the movement of ions from one location to another inside a material. The ions travel through point defects, which are irregularities in the otherwise consistent arrangement of atoms known as the crystal lattice. This sometimes sluggish process can limit the performance and efficiency of fuel cells, batteries, and other energy storage technologies.
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.
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.
OAK RIDGE, Tenn., March 22, 2019 – Karren Leslie More, a researcher at the Department of Energy’s Oak Ridge National Laboratory, has been elected fellow of the Microscopy Society of America (MSA) professional organization.