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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.
In May, the Department of Energy’s Oak Ridge and Brookhaven national laboratories co-hosted the 15th annual International Particle Accelerator Conference, or IPAC, at the Music City Center in Nashville, Tennessee.
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.
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.
Researchers set a new benchmark for future experiments making materials in space rather than for space. They discovered that many kinds of glass have similar atomic structure and arrangements and can successfully be made in space. Scientists from nine institutions in government, academia and industry participated in this 5-year study.
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.