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

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

B3? E4? Remember the board game Battleship? One player suggests a set of coordinates to another, hoping to find the elusive location of an unseen vessel.That is a good place to start in assessing the search for dark matter.

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.

PNNL researchers are developing the only tool that can control large-scale distributed energy resources in real time.

Researchers apply numerical simulations to understand more about a sturdy material and how its basic structure responds to and resists radiation. The outcomes could help guide development of the resilient materials of the future.

A radioactive chemical called pertechnetate is a bad actor when it’s in nuclear waste tanks. But researchers at PNNL and the University of South Florida have a new lead on how to selectively separate it from the nuclear waste for treatment.

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.

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

Installing new access holes (up to 6 feet in diameter) could reduce the overall time and cost to retrieve waste from Hanford's underground storage tanks, according to a structural analysis of the tank domes by PNNL and Becht Engineering.

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.

Peering through the thick, green glass of a decades-old "hot cell," an expert technician manipulates robotic arms to study highly radioactive waste from Hanford, in support of ongoing cleanup.