The Department of Defense has recognized UT-Battelle with a 2022 Secretary of Defense Employer Support Freedom Award, the highest recognition given by the United States government to employers for their support of staff members who serve as reserve members of the U.S. Armed Forces, known collectively as the Reserve component.
Scientists at ORNL have created a miniaturized environment to study the ecosystem around poplar tree roots for insights into plant health and soil carbon sequestration.
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.
Chemical and environmental engineer Samarthya Bhagia is focused on achieving carbon neutrality and a circular economy by designing new plant-based materials for a range of applications from energy storage devices and sensors to environmentally friendly bioplastics.
Though Nell Barber wasn’t sure what her future held after graduating with a bachelor’s degree in psychology, she now uses her interest in human behavior to design systems that leverage machine learning algorithms to identify faces in a crowd.
Scientists at Oak Ridge National Laboratory are closer to unlocking the secrets to better soil carbon sequestration by studying the tiny, sand-like silicon deposits called phytoliths in plants.
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.
How an Alvin M. Weinberg Fellow is increasing security for critical infrastructure components
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.
An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.