Artificial intelligence tools secure tomorrow’s electric grid
A new deep-learning framework developed at ORNL is speeding up the process of inspecting additively manufactured metal parts using X-ray computed tomography, or CT, while increasing the accuracy of the results. The reduced costs for time, labor, maintenance and energy are expected to accelerate expansion of additive manufacturing, or 3D printing.
Tomás Rush began studying the mysteries of fungi in fifth grade and spent his college intern days tromping through forests, swamps and agricultural lands searching for signs of fungal plant pathogens causing disease on host plants.
Researchers at ORNL have developed an online tool that offers industrial plants an easier way to track and download information about their energy footprint and carbon emissions.
Researchers at ORNL explored radium’s chemistry to advance cancer treatments using ionizing radiation.
Five technologies invented by scientists at the Department of Energy’s Oak Ridge National Laboratory have been selected for targeted investment through ORNL’s Technology Innovation Program.
ORNL researchers have developed an upcycling approach that adds value to discarded plastics for reuse in additive manufacturing, or 3D printing.
ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.
How an Alvin M. Weinberg Fellow is increasing security for critical infrastructure components
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
When Andrew Sutton arrived at ORNL in late 2020, he knew the move would be significant in more ways than just a change in location.