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Media Contacts
OAK RIDGE, Tenn., Feb. 19, 2020 — The U.S. Department of Energy’s Oak Ridge National Laboratory and the Tennessee Valley Authority have signed a memorandum of understanding to evaluate a new generation of flexible, cost-effective advanced nuclear reactors.
A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days.
The prospect of simulating a fusion plasma is a step closer to reality thanks to a new computational tool developed by scientists in fusion physics, computer science and mathematics at ORNL.
An international team of researchers has discovered the hydrogen atoms in a metal hydride material are much more tightly spaced than had been predicted for decades — a feature that could possibly facilitate superconductivity at or near room temperature and pressure.
Researchers at Oak Ridge National Laboratory demonstrated that an additively manufactured polymer layer, when applied to carbon fiber reinforced plastic, or CFRP, can serve as an effective protector against aircraft lightning strikes.
The U.S. Department of Energy’s Office of Science announced allocations of supercomputer access to 47 science projects for 2020.
Researchers at the Department of Energy’s Oak Ridge National Laboratory have received five 2019 R&D 100 Awards, increasing the lab’s total to 221 since the award’s inception in 1963.
Using the Titan supercomputer and the Spallation Neutron Source at the Department of Energy’s Oak Ridge National Laboratory, scientists have created the most accurate 3D model yet of an intrinsically disordered protein, revealing the ensemble of its atomic-level structures.
Processes like manufacturing aircraft parts, analyzing data from doctors’ notes and identifying national security threats may seem unrelated, but at the U.S. Department of Energy’s Oak Ridge National Laboratory, artificial intelligence is improving all of these tasks.
In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly.