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Media Contacts
A partnership of ORNL, the Tennessee Department of Economic and Community Development, the Community Reuse Organization of East Tennessee and TVA that aims to attract nuclear energy-related firms to Oak Ridge has been recognized with a state and local economic development award from the Federal Laboratory Consortium.
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.
Oak Ridge National Laboratory researchers have created a technology that more realistically emulates user activities to improve cyber testbeds and ultimately prevent cyberattacks.
Two staff members at the Department of Energy’s Oak Ridge National Laboratory have received prestigious HENAAC and Luminary Awards from Great Minds in STEM, a nonprofit organization that focuses on promoting STEM careers in underserved
The Department of Energy’s Office of Science has selected three Oak Ridge National Laboratory scientists for Early Career Research Program awards.
A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days.
Oak Ridge National Laboratory is training next-generation cameras called dynamic vision sensors, or DVS, to interpret live information—a capability that has applications in robotics and could improve autonomous vehicle sensing.
A detailed study by Oak Ridge National Laboratory estimated how much more—or less—energy United States residents might consume by 2050 relative to predicted shifts in seasonal weather patterns
Researchers at Oak Ridge National Laboratory are taking inspiration from neural networks to create computers that mimic the human brain—a quickly growing field known as neuromorphic computing.
A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool