ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.
A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.
An international problem like climate change needs solutions that cross boundaries, both on maps and among disciplines. Oak Ridge National Laboratory computational scientist Deeksha Rastogi embodies that approach.
A 25-year career with the U.S. Navy, commanding combat missions overseas, brought Tom Kollie back to where he came from — ready to serve his country in a new way.
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
An Oak Ridge National Laboratory researcher has invented a version of an isotope-separating device that can withstand extreme environments, including radiation and chemical solvents.