Energy Secretary Jennifer Granholm visited ORNL on Nov. 22 for a two-hour tour, meeting top scientists and engineers as they highlighted projects and world-leading capabilities that address some of the country’s most complex research and technical challenges.
The U.S. Department of Energy’s Office of Science announced allocations of supercomputer access to 51 high-impact computational science projects for 2022 through its Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program.
A team including researchers from the Department of Energy’s Oak Ridge National Laboratory has developed a digital tool to better monitor a condition known as Barrett’s esophagus, which affects more than 3 million people in the United States.
As a medical isotope, thorium-228 has a lot of potential — and Oak Ridge National Laboratory produces a lot.
Improved data, models and analyses from ORNL scientists and many other researchers in the latest global climate assessment report provide new levels of certainty about what the future holds for the planet
Scientists at ORNL and the University of Wisconsin–Madison have discovered that genetically distinct populations within the same species of fungi can produce unique mixes of secondary metabolites, which are organic compounds with applications in
An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
L&N STEM Academy senior Tyler Duckworth has been named recipient of the 2021 UT-Battelle Scholarship to attend the University of Tennessee.
Belinda Akpa is a chemical engineer with a talent for tackling big challenges and fostering inclusivity and diversity in the next generation of scientists.
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.