ORNL is home to the world's fastest exascale supercomputer, Frontier, which was built in part to facilitate energy-efficient and scalable AI-based algorithms and simulations.
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 hosted its fourth Artificial Intelligence for Robust Engineering and Science, or AIRES, workshop from April 18-20. Over 100 attendees from government, academia and industry convened to identify research challenges and investment areas, carving the future of the discipline.
Mickey Wade has been named associate laboratory director for the Fusion and Fission Energy and Science Directorate at the Department of Energy’s Oak Ridge National Laboratory, effective April 1.
Three researchers at ORNL have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.
Oak Ridge National Laboratory scientists recently demonstrated a low-temperature, safe route to purifying molten chloride salts that minimizes their ability to corrode metals. This method could make the salts useful for storing energy generated from the sun’s heat.
Researchers in the geothermal energy industry are joining forces with fusion experts at ORNL to repurpose gyrotron technology, a tool used in fusion. Gyrotrons produce high-powered microwaves to heat up fusion plasmas.
A force within the supercomputing community, Jack Dongarra developed software packages that became standard in the industry, allowing high-performance computers to become increasingly more powerful in recent decades.
ORNL and the Tennessee Valley Authority, or TVA, are joining forces to advance decarbonization technologies from discovery through deployment through a new memorandum of understanding, or MOU.
Oak Ridge National Laboratory, University of Tennessee and University of Central Florida researchers released a new high-performance computing code designed to more efficiently examine