In the quest for advanced vehicles with higher energy efficiency and ultra-low emissions, ORNL researchers are accelerating a research engine that gives scientists and engineers an unprecedented view inside the atomic-level workings of combustion engines in real time.
Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.
Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS.
Horizon31, LLC has exclusively licensed a novel communication system that allows users to reliably operate unmanned vehicles such as drones from anywhere in the world using only an internet connection.
Five researchers at the Department of Energy’s Oak Ridge National Laboratory have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.
Scientists at ORNL used neutron scattering and supercomputing to better understand how an organic solvent and water work together to break down plant biomass, creating a pathway to significantly improve the production of renewable
A team of researchers has performed the first room-temperature X-ray measurements on the SARS-CoV-2 main protease — the enzyme that enables the virus to reproduce.
Researchers at the Department of Energy’s Oak Ridge National Laboratory are refining their design of a 3D-printed nuclear reactor core, scaling up the additive manufacturing process necessary to build it, and developing methods
The Department of Energy’s Oak Ridge National Laboratory is collaborating with industry on six new projects focused on advancing commercial nuclear energy technologies that offer potential improvements to current nuclear reactors and move new reactor designs closer to deployment.
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the