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Media Contacts
Neutron experiments can take days to complete, requiring researchers to work long shifts to monitor progress and make necessary adjustments. But thanks to advances in artificial intelligence and machine learning, experiments can now be done remotely and in half the time.
Oak Ridge National Laboratory researchers are developing a first-of-its-kind artificial intelligence device for neutron scattering called Hyperspectral Computed Tomography, or HyperCT.
A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.
Four first-of-a-kind 3D-printed fuel assembly brackets, produced at the Department of Energy’s Manufacturing Demonstration Facility at Oak Ridge National Laboratory, have been installed and are now under routine operating
An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.
Algorithms developed at Oak Ridge National Laboratory can greatly enhance X-ray computed tomography images of 3D-printed metal parts, resulting in more accurate, faster scans.
The Transformational Challenge Reactor, or TCR, a microreactor built using 3D printing and other new advanced technologies, could be operational by 2024.
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.