Polyphase wireless power transfer system achieves 270-kilowatt charge, s...
Anyone familiar with ORNL knows it’s a hub for world-class science. The nearly 33,000-acre space surrounding the lab is less known, but also unique.
Oak Ridge National Laboratory worked with Colorado State University to simulate how a warming climate may affect U.S. urban hydrological systems.
Moving to landlocked Tennessee isn’t an obvious choice for most scientists with new doctorate degrees in coastal oceanography.
The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.
Researchers at Oak Ridge National Laboratory have identified a statistical relationship between the growth of cities and the spread of paved surfaces like roads and sidewalks. These impervious surfaces impede the flow of water into the ground, affecting the water cycle and, by extension, the climate.
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.
ORNL has added 10 virtual tours to its campus map, each with multiple views to show floor plans, rotating dollhouse views and 360-degree navigation. As a user travels through a map, pop-out informational windows deliver facts, videos, graphics and links to other related content.
New capabilities and equipment recently installed at the Department of Energy’s Oak Ridge National Laboratory are bringing a creek right into the lab to advance understanding of mercury pollution and accelerate solutions.
Oak Ridge National Laboratory researchers have developed artificial intelligence software for powder bed 3D printers that assesses the quality of parts in real time, without the need for expensive characterization equipment.
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.