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In the wet, muddy places where America’s rivers and lands meet the sea, scientists from the Department of Energy’s Oak Ridge National Laboratory are unearthing clues to better understand how these vital landscapes are evolving under climate change.
Oak Ridge National Laboratory scientists have developed a method leveraging artificial intelligence to accelerate the identification of environmentally friendly solvents for industrial carbon capture, biomass processing, rechargeable batteries and other applications.
Advanced materials research to enable energy-efficient, cost-competitive and environmentally friendly technologies for the United States and Japan is the goal of a memorandum of understanding, or MOU, between the Department of Energy’s Oak Ridge National Laboratory and Japan’s National Institute of Materials Science.
Researchers used quantum simulations to obtain new insights into the nature of neutrinos — the mysterious subatomic particles that abound throughout the universe — and their role in the deaths of massive stars.
Anuj J. Kapadia, who leads the Advanced Computing in Health Sciences Section at the Department of Energy’s Oak Ridge National Laboratory, was named a 2024 Fellow by the American Association of Physicists in Medicine.
Researchers at ORNL and the University of Maine have designed and 3D-printed a single-piece, recyclable natural-material floor panel tested to be strong enough to replace construction materials like steel.
Building innovations from ORNL will be on display in Washington, D.C. on the National Mall June 7 to June 9, 2024, during the U.S. Department of Housing and Urban Development’s Innovation Housing Showcase. For the first time, ORNL’s real-time building evaluator was demonstrated outside of a laboratory setting and deployed for building construction.
John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.
ORNL researchers used electron-beam additive manufacturing to 3D-print the first complex, defect-free tungsten parts with complex geometries.
A team led by researchers at ORNL explored training strategies for one of the largest artificial intelligence models to date with help from the world’s fastest supercomputer. The findings could help guide training for a new generation of AI models for scientific research.