At a conference featuring the most advanced computing hardware and software, ML in its various guises was on full display and highlighted by Nathan Baker’s featured invited presentation.

PNNL and Argonne researchers developed and tested a chemical process that successfully captures radioactive byproducts from used nuclear fuel so they could be sent to advanced reactors for destruction while also producing electrical power.

A new approach developed by PNNL scientists improves the accuracy of patient diagnosis up to 20 percent when compared to other embedding approaches.

Through her role in the Department of Energy’s Advanced Scientific Computing Research-supported ExaLearn project, Jenna Pope is developing deep learning approaches for finding optimal water cluster structures for a variety of applications.

Scientists at PNNL are bringing artificial intelligence into the quest to see whether computers can help humans sift through a sea of experimental data.

The U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) is the recipient of two R&D 100 awards and one gold medal.

In today’s digital age, the rabbit hole of connected information can be not only a time sink, but downright overwhelming. Even for high-performance computers.

Twenty-four analysts from U.S. intelligence organizations met in August for a machine learning activity with PNNL researchers Nicole Nichols, Jeremiah Rounds, Lawrence Phillips, and Brian Kritzstein.

Three powerhouses in the realm of artificial intelligence have become partners in a new research center created by the U.S. Department of Energy.

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.

Xenon search successful! A new scanning transmission electron microscope helps PNNL researchers find xenon deep in a section of nuclear fuel cladding.

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.