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 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.
ORNL was front and center recently at one of the world’s largest optical networking conferences, the 2024 Optic Fiber Communication Conference and Exhibition, or OFC. ORNL researchers had major roles at the OFC 2024, a three-day event held in San Diego, California from March 26-28 which featured thousands of the world’s leading optical communications and networking professionals.
Chuck Greenfield, former assistant director of the DIII-D National Fusion Program at General Atomics, has joined ORNL as ITER R&D Lead.
To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.
Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.
ORNL has added 10 virtual tours to its campus map, each with multiple views to show floor plans, rotating dollhouse views and 360-degree navigation. As a user travels through a map, pop-out informational windows deliver facts, videos, graphics and links to other related content.
An international multi-institution team of scientists has synthesized graphene nanoribbons – ultrathin strips of carbon atoms – on a titanium dioxide surface using an atomically precise method that removes a barrier for custom-designed carbon
Researchers at ORNL used quantum optics to advance state-of-the-art microscopy and illuminate a path to detecting material properties with greater sensitivity than is possible with traditional tools.
Oak Ridge National Laboratory researchers have developed artificial intelligence software for powder bed 3D printers that assesses the quality of parts in real time, without the need for expensive characterization equipment.