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Media Contacts
Six firms received Small Business Awards from the Department of Energy’s Oak Ridge National Laboratory. The companies, selected from small business service providers to the lab, were recognized by ORNL's Small Business Programs Office for their specific capabilities and contributions.
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.
Momentum for manufacturing innovation in the United States got a boost during the inaugural MDF Innovation Days, held recently at the U.S. Department of Energy Manufacturing Demonstration Facility at Oak Ridge National Laboratory.
ORNL scientists develop a sample holder that tumbles powdered photochemical materials within a neutron beamline — exposing more of the material to light for increased photo-activation and better photochemistry data capture.
ORNL researchers used electron-beam additive manufacturing to 3D-print the first complex, defect-free tungsten parts with complex geometries.
Researchers at ORNL are developing battery technologies to fight climate change in two ways, by expanding the use of renewable energy and capturing airborne carbon dioxide.
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.