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Media Contacts
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
Scientists at ORNL used their expertise in quantum biology, artificial intelligence and bioengineering to improve how CRISPR Cas9 genome editing tools work on organisms like microbes that can be modified to produce renewable fuels and chemicals.
As current courses through a battery, its materials erode over time. Mechanical influences such as stress and strain affect this trajectory, although their impacts on battery efficacy and longevity are not fully understood.
The Department of Energy’s Oak Ridge National Laboratory announced the establishment of the Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making.
Wildfires are an ancient force shaping the environment, but they have grown in frequency, range and intensity in response to a changing climate. At ORNL, scientists are working on several fronts to better understand and predict these events and what they mean for the carbon cycle and biodiversity.
Innovations in artificial intelligence are rapidly shaping our world, from virtual assistants and chatbots to self-driving cars and automated manufacturing.
Shih-Chieh Kao, manager of the Water Power program at ORNL, has been named a fellow of the American Society of Civil Engineer’s Environmental & Water Resources Institute, or EWRI.
Colleen Iversen, ecosystem ecologist, group leader and distinguished staff scientist, has been named director of the Next-Generation Ecosystem Experiments Arctic, or NGEE Arctic, a multi-institutional project studying permafrost thaw and other climate-related processes in Alaska.
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.
Oak Ridge National Laboratory scientists set out to address one of the biggest uncertainties about how carbon-rich permafrost will respond to gradual sinking of the land surface as temperatures rise.