Artificial intelligence tools secure tomorrow’s electric grid
ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.
A force within the supercomputing community, Jack Dongarra developed software packages that became standard in the industry, allowing high-performance computers to become increasingly more powerful in recent decades.
Scientists’ increasing mastery of quantum mechanics is heralding a new age of innovation. Technologies that harness the power of nature’s most minute scale show enormous potential across the scientific spectrum
Surrounded by the mountains of landlocked Tennessee, Oak Ridge National Laboratory’s Teri O’Meara is focused on understanding the future of the vitally important ecosystems lining the nation’s coasts.
To study how space radiation affects materials for spacecraft and satellites, Oak Ridge National Laboratory scientists sent samples to the International Space Station. The results will inform design of radiation-resistant magnetic and electronic systems.
ORNL and the Tennessee Valley Authority, or TVA, are joining forces to advance decarbonization technologies from discovery through deployment through a new memorandum of understanding, or MOU.
A study led by researchers at ORNL used the nation’s fastest supercomputer to close in on the answer to a central question of modern physics that could help conduct development of the next generation of energy technologies.
A new fusion record was announced February 9 in the United Kingdom: At the Joint European Torus, or JET, the team documented the generation of 59 megajoules of sustained fusion energy, more than doubling the
ORNL, TVA and TNECD were recognized by the Federal Laboratory Consortium for their impactful partnership that resulted in a record $2.3 billion investment by Ultium Cells, a General Motors and LG Energy Solution joint venture, to build a battery cell manufacturing plant in Spring Hill, Tennessee.
Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity.