Quantum precision reached in modeling molten salt behavior
In fiscal year 2023 — Oct. 1–Sept. 30, 2023 — Oak Ridge National Laboratory was awarded more than $8 million in technology maturation funding through the Department of Energy’s Technology Commercialization Fund, or TCF.
ORNL, a bastion of nuclear physics research for the past 80 years, is poised to strengthen its programs and service to the United States over the next decade if national recommendations of the Nuclear Science Advisory Committee, or NSAC, are enacted.
ORNL is leading two nuclear physics research projects within the Scientific Discovery through Advanced Computing, or SciDAC, program from the Department of Energy Office of Science.
Few things carry the same aura of mystery as dark matter. The name itself radiates secrecy, suggesting something hidden in the shadows of the Universe.
Andrea Delgado is looking for elementary particles that seem so abstract, there appears to be no obvious short-term benefit to her research.
The old photos show her casually writing data in a logbook with stacks of lead bricks nearby, or sealing a vacuum chamber with a wrench. ORNL researcher Frances Pleasonton was instrumental in some of the earliest explorations of the properties of the neutron as the X-10 Site was finding its postwar footing as a research lab.
For nearly six years, the Majorana Demonstrator quietly listened to the universe. Nearly a mile underground at the Sanford Underground Research Facility, or SURF, in Lead, South Dakota, the experiment collected data that could answer one of the most perplexing questions in physics: Why is the universe filled with something instead of nothing?
Researchers at ORNL are tackling a global water challenge with a unique material designed to target not one, but two toxic, heavy metal pollutants for simultaneous removal.
Two decades in the making, a new flagship facility for nuclear physics opened on May 2, and scientists from the Department of Energy’s Oak Ridge National Laboratory have a hand in 10 of its first 34 experiments.
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.