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.

A staple in horror movies, flickering lights can also summon potential human health and productivity concerns. PNNL studied hand-held meters that measure flicker, and the results could improve future measurement and lighting strategies.

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.

Researchers at PNNL construct a novel approach that requires less field work while delivering critical information on building code compliance and energy efficiency in new homes.

PNNL’s Solid State Lighting program evaluated the energy and photometric performance of adjustable LED lighting systems installed in three California classrooms as part of a GATEWAY study.

A PNNL researcher peers into the future and sees homes and neighborhoods seamlessly working together to coordinate energy use.

Following the energy crisis of 2000-2001, the State of Washington received financial settlements from six energy companies, a fraction of which was used for energy-efficiency research.

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.

PNNL's VOLTTRON is available to developers as part of the Eclipse Foundation.

Scientists are exploring the use of deep neural network to interpret highly technical data related to national security, the environment and the cosmos.