When the Department of Energy’s Oak Ridge National Laboratory science mission takes staff off-campus, the lab’s safety principles follow. That’s true even in the high mountain passes of Washington and Oregon, where ORNL scientists are tracking a tree species — and where wildfires have become more frequent and widespread.
Researchers at ORNL and the University of Maine have designed and 3D-printed a single-piece, recyclable natural-material floor panel tested to be strong enough to replace construction materials like steel.
Erin Webb, lead for the Bioresources Science and Engineering group at Oak Ridge National Laboratory, has been elected a Fellow of the American Society of Agricultural and Biological Engineers — the society’s highest honor.
Researchers at the Department of Energy’s Oak Ridge National Laboratory met recently at an AI Summit to better understand threats surrounding artificial intelligence. The event was part of ORNL’s mission to shape the future of safe and secure AI systems charged with our nation’s most precious data.
A team led by researchers at ORNL explored training strategies for one of the largest artificial intelligence models to date with help from the world’s fastest supercomputer. The findings could help guide training for a new generation of AI models for scientific research.
When scientists pushed the world’s fastest supercomputer to its limits, they found those limits stretched beyond even their biggest expectations. In the latest milestone, a team of engineers and scientists used Frontier to simulate a system of nearly half a trillion atoms — the largest system ever modeled and more than 400 times the size of the closest competition.
ORNL researchers have teamed up with other national labs to develop a free platform called Open Energy Data Initiative Solar Systems Integration Data and Modeling to better analyze the behavior of electric grids incorporating many solar projects.
Four ORNL researchers traveled to Warsaw, Poland, during the first week of April to support the opening of Poland’s first Clean Energy Training Center, a regional hub dedicated to providing workforce development and training to expand new nuclear
Researchers at ORNL are using a machine-learning model to answer ‘what if’ questions stemming from major events that impact large numbers of people. By simulating an event, such as extreme weather, researchers can see how people might respond to adverse situations, and those outcomes can be used to improve emergency planning.
To balance personal safety and research innovation, researchers at ORNL are employing a mathematical technique known as differential privacy to provide data privacy guarantees.