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Media Contacts
Researchers at Oak Ridge National Laboratory have designed architecture, software and control strategies for a futuristic EV truck stop that can draw megawatts of power and reduce carbon emissions.
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.
John “Jack” Cahill is out to illuminate previously unseen processes with new technology, advancing our understanding of how chemicals interact to influence complex systems whether it’s in the human body or in the world beneath our feet.
Having lived on three continents spanning the world’s four hemispheres, Philipe Ambrozio Dias understands the difficulties of moving to a new place.
Oak Ridge National Laboratory scientists recently demonstrated a low-temperature, safe route to purifying molten chloride salts that minimizes their ability to corrode metals. This method could make the salts useful for storing energy generated from the sun’s heat.
Scientists at Oak Ridge National Laboratory are using ultrasounds — usually associated with medical imaging — to check the health of an operating battery. The technique uses sensors as small as a thumbnail, which could be attached to a lithium-ion battery inside a car.
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.
Mechanical engineer Marm Dixit’s work is all about getting electricity to flow efficiently from one end of a solid-state battery to the other. It’s a high-stakes problem
Jennifer Morrell-Falvey’s interest in visualizing the science behind natural processes was what drew her to ORNL in what she expected to be a short stint some 18 years ago.
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.