Katy Bradford: Cassette approach offers compelling construction solution
Working with Western Michigan University and other partners, ORNL engineers are placing low-powered sensors in the reflective raised pavement markers that are already used to help drivers identify lanes. Microchips inside the markers transmit information to passing cars about the road shape to help autonomous driving features function even when vehicle cameras or remote laser sensing, called LiDAR, are unreliable because of fog, snow, glare or other obstructions.
In a discovery aimed at accelerating the development of process-advantaged crops for jet biofuels, scientists at ORNL developed a capability to insert multiple genes into plants in a single step.
ORNL scientists found that a small tweak created big performance improvements in a type of solid-state battery, a technology considered vital to broader electric vehicle adoption.
An innovative and sustainable chemistry developed at ORNL for capturing carbon dioxide has been licensed to Holocene, a Knoxville-based startup focused on designing and building plants that remove carbon dioxide
Colleen Iversen, ecosystem ecologist, group leader and distinguished staff scientist, has been named director of the Next-Generation Ecosystem Experiments Arctic, or NGEE Arctic, a multi-institutional project studying permafrost thaw and other climate-related processes in Alaska.
Oak Ridge National Laboratory scientists led the development of a supply chain model revealing the optimal places to site farms, biorefineries, pipelines and other infrastructure for sustainable aviation fuel production.
SAE International has awarded ORNL Buildings and Transportation Science Division Director Robert Wagner with the SAE Medal of Honor for his dedication and support of the organization’s mission of advancing mobility solutions.
Andrew Lupini, a scientist and inventor at ORNL, has been elected Fellow of the Microscopy Society of America.
Oak Ridge National Laboratory scientists exploring bioenergy plant genetics have made a surprising discovery: a protein domain that could lead to new COVID-19 treatments.
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.