News

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.

Two scientists with the Department of Energy’s Oak Ridge National Laboratory have been elected fellows of the American Physical Society.

Scientists at Oak Ridge National Laboratory and the University of Tennessee designed and demonstrated a method to make carbon-based materials that can be used as electrodes compatible with a specific semiconductor circuitry.

Led by ORNL and the University of Tennessee, Knoxville, a study of a solar-energy material with a bright future revealed a way to slow phonons, the waves that transport heat.

For over half a century, Robert Compton has been a celebrated experimentalist and inspirational leader and teacher in the fields of physics and chemistry. Compton came to work at ORNL's Health Sciences Research Division in 1965 after receiving his doctorate in physics from the University of Tennessee.

Sheldon Datz's 50-year career as an innovator in the fields of chemistry and atomic physics at ORNL was defined by his knack for seeing the big picture and his ability to synthesize and expand upon developments across diverse disciplines.

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.

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.

An all-in-one experimental platform developed at Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences accelerates research on promising materials for future technologies.

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.