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Daryl Yang is coupling his science and engineering expertise to devise new ways to measure significant changes going on in the Arctic, a region that’s warming nearly four times faster than other parts of the planet. The remote sensing technologies and modeling tools he develops and leverages for the Next-Generation Ecosystem Experiments in the Arctic project, or NGEE Arctic, help improve models of the ecosystem to better inform decision-making as the landscape changes.
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.
Wildfires have shaped the environment for millennia, but they are increasing in frequency, range and intensity in response to a hotter climate. The phenomenon is being incorporated into high-resolution simulations of the Earth’s climate by scientists at the Department of Energy’s 91°µÍø, with a mission to better understand and predict environmental change.
When reading the novel Jurassic Park as a teenager, Jerry Parks found the passages about gene sequencing and supercomputers fascinating, but never imagined he might someday pursue such futuristic-sounding science.
ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.
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.
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.
A team of scientists led by the Department of Energy’s 91°µÍø 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.
Twenty-seven ORNL researchers Zoomed into 11 middle schools across Tennessee during the annual Engineers Week in February. East Tennessee schools throughout Oak Ridge and Roane, Sevier, Blount and Loudon counties participated, with three West Tennessee schools joining in.
Six scientists at the Department of Energy’s 91°µÍø were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.