ORNL and the University of Tennessee, Knoxville, co-hosted the 2023 National Society of Black Physicists Annual Conference with the theme "Frontiers in Physics: From Quantum to Materials to the Cosmos.” As part of the three-day conference held near UT, attendees took a 30-mile trip to the ORNL campus for facility tours, science talks and workshops.
From July 15 to 26, 2024, the Department of Energy’s Oak Ridge National Laboratory will host the second U.S. Quantum Information Science, or QIS, Summer School.
New computational framework speeds discovery of fungal metabolites, key to plant health and used in drug therapies and for other uses.
ORNL’s successes in QIS and its forward-looking strategy were recently recognized in the form of three funding awards that will help ensure the laboratory remains a leader in advancing quantum computers and networks.
In summer 2023, ORNL's Prasanna Balaprakash was invited to speak at a roundtable discussion focused on the importance of academic artificial intelligence research and development hosted by the White House Office of Science and Technology Policy and the U.S. National Science Foundation.
The 2023 top science achievements from HFIR and SNS feature a broad range of materials research published in high impact journals such as Nature and Advanced Materials.
The U.S. Department of Energy’s Oak Ridge Leadership Computing Facility has informed the recipients of high-performance computing time through the SummitPLUS allocation program, which extends the operation of the Summit supercomputer through October 2024.
ORNL will lead a new DOE-funded project designed to accelerate bringing fusion energy to the grid. The Accelerate award focuses on developing a fusion power plant design concept that supports remote maintenance and repair methods for the plasma-facing components in fusion power plants.
Two fusion energy leaders have joined ORNL in the Fusion and Fission Energy and Science Directorate, or FFESD.
A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%.