Researchers at Oak Ridge National Laboratory proved that a certain class of ionic liquids, when mixed with commercially available oils, can make gears run more efficiently with less noise and better durability.
More than 6,000 veterans died by suicide in 2016, and from 2005 to 2016, the rate of veteran suicides in the United States increased by more than 25 percent.
Using the Titan supercomputer at Oak Ridge National Laboratory, a team of astrophysicists created a set of galactic wind simulations of the highest resolution ever performed. The simulations will allow researchers to gather and interpret more accurate, detailed data that elucidates how galactic winds affect the formation and evolution of galaxies.
A team of researchers at Oak Ridge National Laboratory have demonstrated that designed synthetic polymers can serve as a high-performance binding material for next-generation lithium-ion batteries.
Scientists have discovered a way to alter heat transport in thermoelectric materials, a finding that may ultimately improve energy efficiency as the materials
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—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
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 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.