Polyphase wireless power transfer system achieves 270-kilowatt charge, s...
When Kashif Nawaz looks at a satellite map of the U.S., he sees millions of buildings that could hold a potential solution for the capture of carbon dioxide, a plentiful gas that can be harmful when excessive amounts are released into the atmosphere, raising the Earth’s temperature.
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.
Xin Sun has been selected as the associate laboratory director for the Energy Science and Technology Directorate, or ESTD, at the Department of Energy’s Oak Ridge National Laboratory.
Researchers at Oak Ridge National Laboratory developed self-healing elastomers that demonstrated unprecedented adhesion strength and the ability to adhere to many surfaces, which could broaden their potential use
A new tool from Oak Ridge National Laboratory can help planners, emergency responders and scientists visualize how flood waters will spread for any scenario and terrain.
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.
Four research teams from the Department of Energy’s Oak Ridge National Laboratory and their technologies have received 2020 R&D 100 Awards.
ORNL and Department of Energy officials dedicated the launch of two clean energy research initiatives that focus on the recycling and recovery of advanced manufacturing materials and on connected and
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.