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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.
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 group of high school graduates and community college students visited ORNL to meet staff and find out just what goes on at a DOE national laboratory. The Job Shadow Day was arranged by tnAchieves, a student support organization that works to increase higher educational opportunities for students across Tennessee through scholarships and mentorship.
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.
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.