Gina Tourassi has been appointed as director of the National Center for Computational Sciences, a division of the Computing and Computational Sciences Directorate at Oak Ridge National Laboratory.
Scientists at the U.S. Department of Energy’s Brookhaven National Laboratory have new experimental evidence and a predictive theory that solves a long-standing materials science mystery: why certain crystalline materials shrink when heated.
ORNL and The University of Toledo have entered into a memorandum of understanding for collaborative research.
Quanex Building Products has signed a non-exclusive agreement to license a method to produce insulating material from ORNL. The low-cost material can be used as an additive to increase thermal insulation performance and improve energy efficiency when applied to a variety of building products.
A team led by scientists at the Department of Energy’s Oak Ridge National Laboratory explored how atomically thin two-dimensional (2D) crystals can grow over 3D objects and how the curvature of those objects can stretch and strain the
An ORNL-led team's observation of certain crystalline ice phases challenges accepted theories about super-cooled water and non-crystalline ice. Their findings, reported in the journal Nature, will also lead to better understanding of ice and its various phases found on other planets, moons and elsewhere in space.
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.
OAK RIDGE, Tenn., May 7, 2019—Energy Secretary Rick Perry, Congressman Chuck Fleischmann and lab officials today broke ground on a multipurpose research facility that will provide state-of-the-art laboratory space
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.