Groundwater withdrawals are expected to peak in about one-third of the world’s basins by 2050, potentially triggering significant trade and agriculture shifts, a new analysis finds.
ORNL's Scott Curran, group leader for Fuel Science and Engine Technologies Research, has been named a fellow of SAE International and ASME.
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.
Thomas Proffen, a neutron scattering scientist at ORNL and founder of Oak Ridge Computer Science Girls, was recognized with an award from the National Center for Women & Information Technology, or NCWIT. In addition, one of his students received a national honor from the organization.
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.
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.
Forrest Hoffman, a distinguished scientist at the Department of Energy’s Oak Ridge National Laboratory, has been named a senior member of the Institute of Electrical and Electronics Engineers, the world’s largest organization for technical professionals.
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.