Trouble on the electric grid might start with something relatively small: a downed power line, or a lightning strike at a substation. What happens next?
Pacific Northwest National Laboratory is leading efforts to address next-generation computing’s critical role in protecting the nation from cybersecurity threats.
Researchers at PNNL are applying deep learning techniques to learn more about neutrinos, part of a worldwide network of researchers trying to understand one of the universe’s most elusive particles.
It’s hot in there! PNNL researchers take a close, but nonradioactive, look at metal particle formation in a nuclear fuel surrogate material. What they found will help fill knowledge gaps and could lead to better nuclear fuel designs.
Josef "Pepa" Matyas, a materials scientist in PNNL’s Nuclear Sciences Division, has been elected a fellow of the American Ceramic Society (ACerS). He will be recognized at the ACerS annual meeting on September 30, 2019, in Portland, Ore.
Scientists created a fast-track tutorial that equips a neural network to tackle drug discovery and other applications where there's a shortage of precisely labeled chemical data.
Researchers used novel methods to safely create and analyze plutonium samples. The approaches could prove influential in future studies of the radioactive material, benefitting research in legacy, national security and nuclear fuels.
Scientists are exploring the use of deep neural network to interpret highly technical data related to national security, the environment and the cosmos.
