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Media Contacts
Marc-Antoni Racing has licensed a collection of patented energy storage technologies developed at ORNL. The technologies focus on components that enable fast-charging, energy-dense batteries for electric and hybrid vehicles and grid storage.
When Bill Partridge started working with industry partner Cummins in 1997, he was a postdoctoral researcher specializing in applied optical diagnostics and new to Oak Ridge National Laboratory.
ORNL has been selected to lead an Energy Frontier Research Center, or EFRC, focused on polymer electrolytes for next-generation energy storage devices such as fuel cells and solid-state electric vehicle batteries.
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.
Burak Ozpineci, a Corporate Fellow and section head for Vehicle and Mobility Systems Research at Oak Ridge National Laboratory, is one of six international recipients of the eighth Nagamori Award.
ORNL researchers have developed an upcycling approach that adds value to discarded plastics for reuse in additive manufacturing, or 3D printing.
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.
It’s been referenced in Popular Science and Newsweek, cited in the Economic Report of the President, and used by agencies to create countless federal regulations.
Oak Ridge National Laboratory researchers determined that for every 5 miles per hour that drivers travel over a 50-mph speed limit, fuel economy decreases by 7% and equates to paying an extra 28 cents per gallon at current.
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.