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Media Contacts
Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.
Currently, the biggest hurdle for electric vehicles, or EVs, is the development of advanced battery technology to extend driving range, safety and reliability.
Neutron experiments can take days to complete, requiring researchers to work long shifts to monitor progress and make necessary adjustments. But thanks to advances in artificial intelligence and machine learning, experiments can now be done remotely and in half the time.
Cody Lloyd became a nuclear engineer because of his interest in the Manhattan Project, the United States’ mission to advance nuclear science to end World War II. As a research associate in nuclear forensics at ORNL, Lloyd now teaches computers to interpret data from imagery of nuclear weapons tests from the 1950s and early 1960s, bringing his childhood fascination into his career
After completing a bachelor’s degree in biology, Toya Beiswenger didn’t intend to go into forensics. But almost two decades later, the nuclear security scientist at ORNL has found a way to appreciate the art of nuclear forensics.
When geoinformatics engineering researchers at the Department of Energy’s Oak Ridge National Laboratory wanted to better understand changes in land areas and points of interest around the world, they turned to the locals — their data, at least.
Nonfood, plant-based biofuels have potential as a green alternative to fossil fuels, but the enzymes required for production are too inefficient and costly to produce. However, new research is shining a light on enzymes from fungi that could make biofuels economically viable.
Having lived on three continents spanning the world’s four hemispheres, Philipe Ambrozio Dias understands the difficulties of moving to a new place.
When the COVID-19 pandemic stunned the world in 2020, researchers at ORNL wondered how they could extend their support and help
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.