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Media Contacts
ORNL and Caterpillar Inc. have entered into a cooperative research and development agreement, or CRADA, to investigate using methanol as an alternative fuel source for four-stroke internal combustion marine engines.
Scientists from Stanford University and the Department of Energy’s Oak Ridge National Laboratory are turning air into fertilizer without leaving a carbon footprint. Their discovery could deliver a much-needed solution to help meet worldwide carbon-neutral goals by 2050.
Within the Department of Energy’s National Transportation Research Center at ORNL’s Hardin Valley Campus, scientists investigate engines designed to help the U.S. pivot to a clean mobility future.
Effective Dec. 4, Gina Tourassi will assume responsibilities as associate laboratory director for the Computing and Computational Sciences Directorate at the Department of Energy’s Oak Ridge National Laboratory.
Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.
How do you get water to float in midair? With a WAND2, of course. But it’s hardly magic. In fact, it’s a scientific device used by scientists to study matter.
ORNL is home to the world's fastest exascale supercomputer, Frontier, which was built in part to facilitate energy-efficient and scalable AI-based algorithms and simulations.
Used lithium-ion batteries from cell phones, laptops and a growing number of electric vehicles are piling up, but options for recycling them remain limited mostly to burning or chemically dissolving shredded batteries.
The first climate scientist to head the Department of Energy’s Office of Science, Dr. Asmeret Asefaw Berhe, recently visited two ORNL-led field research facilities in Minnesota and Alaska to witness how these critically important projects are informing our understanding of the future climate and its impact on communities.
ORNL has joined a global consortium of scientists from federal laboratories, research institutes, academia and industry to address the challenges of building large-scale artificial intelligence systems and advancing trustworthy and reliable AI for