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.
An international team using neutrons set the first benchmark (one nanosecond) for a polymer-electrolyte and lithium-salt mixture. Findings could produce safer, more powerful lithium batteries.
The Neutron Scattering Society of America, or NSSA, recognized Oak Ridge National Laboratory’s Ke An and Ken Herwig as fellows for their outstanding contributions to neutron scattering.
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.
Jens Dilling has been named associate laboratory director for the Neutron Sciences Directorate at the Department of Energy’s Oak Ridge National Laboratory, effective April 1.
Scientists at ORNL have developed 3D-printed collimator techniques that can be used to custom design collimators that better filter out noise during different types of neutron scattering experiments
Astrophysicists at the State University of New York, Stony Brook and University of California, Berkeley, used the Oak Ridge Leadership Computing Facility’s Summit supercomputer to compare models of X-ray bursts in 2D and 3D.
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.
In partnership with the National Cancer Institute, researchers from the Department of Energy’s Oak Ridge National Laboratory’s Modeling Outcomes for Surveillance using Scalable Artificial Intelligence are building on their groundbreaking work to