Artificial intelligence tools secure tomorrow’s electric grid
New computational framework speeds discovery of fungal metabolites, key to plant health and used in drug therapies and for other uses.
Technology Transfer staff from Department of Energy’s Oak Ridge National Laboratory attended the 2024 Consumer Electronics Show, or CES, in Las Vegas, Jan. 8–12.
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 21st Symposium on Separation Science and Technology for Energy Applications, Oct. 23-26 at the Embassy Suites by Hilton West in Knoxville, attracted 109 researchers, including some from Austria and the Czech Republic. Besides attending many technical sessions, they had the opportunity to tour the Graphite Reactor, High Flux Isotope Reactor and both supercomputers at ORNL.
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.
Ateios Systems licensed an ORNL technology for solvent-free battery component production using electron curing. Through Innovation Crossroads, Ateios continues to work with ORNL to enable readiness for production-quality battery components.
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%.
A team of computational scientists at ORNL has generated and released datasets of unprecedented scale that provide the ultraviolet visible spectral properties of over 10 million organic molecules.
A team of eight scientists won the Association for Computing Machinery’s 2023 Gordon Bell Prize for their study that used the world’s first exascale supercomputer to run one of the largest simulations of an alloy ever and achieve near-quantum accuracy.
Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.