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A new study conducted on the Frontier supercomputer gave researchers new clues to improving fusion confinement. This research, in collaboration with General Atomics and UC San Diego, uncovered that the interaction between ions and electrons near the tokamak's edge can unexpectedly increase turbulence, challenging previous assumptions about how to optimize plasma confinement for efficient nuclear fusion.
ORNL researchers completed successful testing of a gallium nitride transistor for use in more accurate sensors operating near the core of a nuclear reactor. This is an important technical advance particularly for monitoring new, compact.
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.
An Oak Ridge National Laboratory team revealed how chemical species form in a highly reactive molten salt mixture of aluminum chloride and potassium chloride by unraveling vibrational signatures and observing ion exchanges.
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.
Oak Ridge National Laboratory scientists ingeniously created a sustainable, soft material by combining rubber with woody reinforcements and incorporating “smart” linkages between the components that unlock on demand.
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.
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.
When scientists pushed the world’s fastest supercomputer to its limits, they found those limits stretched beyond even their biggest expectations. In the latest milestone, a team of engineers and scientists used Frontier to simulate a system of nearly half a trillion atoms — the largest system ever modeled and more than 400 times the size of the closest competition.