Polyphase wireless power transfer system achieves 270-kilowatt charge, s...
A collaboration between the ORNL and a Florida-based medical device manufacturer has led to the addition of 500 jobs in the Miami area to support the mass production of N95 respirator masks.
An international multi-institution team of scientists has synthesized graphene nanoribbons – ultrathin strips of carbon atoms – on a titanium dioxide surface using an atomically precise method that removes a barrier for custom-designed carbon
Growing up in Florida, Emma Betters was fascinated by rockets and for good reason. Any time she wanted to see a space shuttle launch from NASA’s nearby Kennedy Space Center, all she had to do was sit on her front porch.
Scientists at ORNL and the University of Nebraska have developed an easier way to generate electrons for nanoscale imaging and sensing, providing a useful new tool for material science, bioimaging and fundamental quantum research.
ORNL scientists have modified a single microbe to simultaneously digest five of the most abundant components of lignocellulosic biomass, a big step forward in the development of a cost-effective biochemical conversion process to turn plants into
Kübra Yeter-Aydeniz, a postdoctoral researcher, was recently named the Turkish Women in Science group’s “Scientist of the Week.”
Experts at the Department of Energy’s Oak Ridge National Laboratory are now offering short-term technical and scientific assistance to entities working to combat the coronavirus through the COVID-19 Technical Assistance Program, an initiative of DOE’s Office of Technology Transitions.
Researchers at ORNL used quantum optics to advance state-of-the-art microscopy and illuminate a path to detecting material properties with greater sensitivity than is possible with traditional tools.
The Department of Energy has selected Oak Ridge National Laboratory to lead a collaboration charged with developing quantum technologies that will usher in a new era of innovation.
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.