Updated software improves slicing for large-format 3D printing
Oak Ridge National Laboratory researchers serendipitously discovered when they automated the beam of an electron microscope to precisely drill holes in the atomically thin lattice of graphene, the drilled holes closed up.
ORNL researchers are deploying their broad expertise in climate data and modeling to create science-based mitigation strategies for cities stressed by climate change as part of two U.S. Department of Energy Urban Integrated Field Laboratory projects.
A crowd of investors and supporters turned out for last week’s Innovation Crossroads Showcase at the Knoxville Chamber as part of Innov865 Week. Sponsored by ORNL and the Tennessee Advanced Energy Business Council, the event celebrated deep-tech entrepreneurs and the Oak Ridge Corridor as a growing energy innovation hub for the nation.
Researchers at ORNL explored radium’s chemistry to advance cancer treatments using ionizing radiation.
Larry Allard, a distinguished research staff member at Oak Ridge National Laboratory, has been named a Fellow of the Microanalysis Society.
Researchers at ORNL are tackling a global water challenge with a unique material designed to target not one, but two toxic, heavy metal pollutants for simultaneous removal.
To optimize biomaterials for reliable, cost-effective paper production, building construction, and biofuel development, researchers often study the structure of plant cells using techniques such as freezing plant samples or placing them in a vacuum.
Two decades in the making, a new flagship facility for nuclear physics opened on May 2, and scientists from the Department of Energy’s Oak Ridge National Laboratory have a hand in 10 of its first 34 experiments.
What’s getting Jim Szybist fired up these days? It’s the opportunity to apply his years of alternative fuel combustion and thermodynamics research to the challenge of cleaning up the hard-to-decarbonize, heavy-duty mobility sector — from airplanes to locomotives to ships and massive farm combines.
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.