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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.
ORNL researchers discovered genetic mutations that underlie autism using a new approach that could lead to better diagnostics and drug therapies.
Neutron scattering techniques were used as part of a study of a novel nanoreactor material that grows crystalline hydrogen clathrates, or HCs, capable of storing hydrogen.
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.
A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.
Oak Ridge National Laboratory researchers are developing a first-of-its-kind artificial intelligence device for neutron scattering called Hyperspectral Computed Tomography, or HyperCT.
Researchers at Oak Ridge National Laboratory are using state-of-the-art methods to shed light on chemical separations needed to recover rare-earth elements and secure critical materials for clean energy technologies.
Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.