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Media Contacts
ORNL researchers modeled how hurricane cloud cover would affect solar energy generation as a storm followed 10 possible trajectories over the Caribbean and Southern U.S.
Scientists at ORNL have developed a method that demonstrates how fiber-reinforced polymer composite materials used in the automotive, aerospace and renewable energy industries can be made stronger and tougher to better withstand mechanical or structural stresses over time.
ORNL’s Omer Onar and Mostak Mohammad will present on ORNL's wireless charging technology in DOE’s Office of Technology Transitions National Lab Discovery Series Tuesday, April 30.
Held in Cocoa Beach, Florida from March 11 to 14, researchers across the computing and data spectra participated in sessions developed by staff members from the Department of Energy’s Oak Ridge National Laboratory, or ORNL, Sandia National Laboratories and the Swiss National Supercomputing Centre.
ORNL’s Erin Webb is co-leading a new Circular Bioeconomy Systems Convergent Research Initiative focused on advancing production and use of renewable carbon from Tennessee to meet societal needs.
In the age of easy access to generative AI software, user can take steps to stay safe. Suhas Sreehari, an applied mathematician, identifies misconceptions of generative AI that could lead to unintentionally bad outcomes for a user.
ORNL researchers are working to make EV charging more resilient by developing algorithms to deal with both internal and external triggers of charger failure. This will help charging stations remain available to traveling EV drivers, reducing range anxiety.
Scientists at ORNL have developed 3-D-printed collimator techniques that can be used to custom design collimators that better filter out noise during different types of neutron scattering experiments
The Department of Energy’s Oak Ridge National Laboratory is providing national leadership in a new collaboration among five national laboratories to accelerate U.S. production of clean hydrogen fuel cells and electrolyzers.
In partnership with the National Cancer Institute, researchers from ORNL and Louisiana State University developed a long-sequenced AI transformer capable of processing millions of pathology reports to provide experts researching cancer diagnoses and management with exponentially more accurate information on cancer reporting.