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Media Contacts
Seven scientists at the Department of Energy’s Oak Ridge National Laboratory have been named Battelle Distinguished Inventors, in recognition of their obtaining 14 or more patents during their careers at the lab.
The presence of minerals called ash in plants makes little difference to the fitness of new naturally derived compound materials designed for additive manufacturing, an Oak Ridge National Laboratory-led team found.
ORNL researchers discovered genetic mutations that underlie autism using a new approach that could lead to better diagnostics and drug therapies.
Five technologies invented by scientists at the Department of Energy’s Oak Ridge National Laboratory have been selected for targeted investment through ORNL’s Technology Innovation Program.
Scientists develop environmental justice lens to identify neighborhoods vulnerable to climate change
A new capability to identify urban neighborhoods, down to the block and building level, that are most vulnerable to climate change could help ensure that mitigation and resilience programs reach the people who need them the most.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
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.
Oak Ridge National Laboratory researchers recently used large-scale additive manufacturing with metal to produce a full-strength steel component for a wind turbine, proving the technique as a viable alternative to
Three ORNL scientists have been elected fellows of the American Association for the Advancement of Science, or AAAS, the world’s largest general scientific society and publisher of the Science family of journals.
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.