The Scientific Discovery through Advanced Computing institute will focus on making scientific machine learning accessible to domain scientists.

The Genesis Mission will mobilize the Department of Energy’s 17 National Laboratories, industry, and academia to build an integrated discovery platform.

PNNL brings its expertise to the space domain by joining an organization that facilitates collaboration across the global space industry.

This achievement earned DIMPLES a Best Paper award at the ACM International Conference on Supercomputing 2025.

As Laboratory Director Steve Ashby pens his last monthly column, he highlights PNNL’s accomplishments with pride and gratitude.

A breakthrough at PNNL could free friction stir from current constraints—and open the door for increased use of the advanced manufacturing technique on commercial assembly lines.

Micron and PNNL co-design the Crete computer system, delivering a new memory architecture for data-intensive scientific computing and AI applications.

Through an unprecedented collaboration with Idaho, Savannah River, and Argonne national laboratories, the Athena Project has built a network of nearly 150 scientists.

Researchers have begun a series of experiments that could bring about more energy for grid, thanks to a special delivery of 11 "high burnup" rods.

Scientists have tapped AI and powerful computing to speed up how quickly officials are able to learn important details about nuclear events.

Patricia Paviet has led 100+ international webinars, building a vital global resource for next-generation nuclear energy education and collaboration.

Researchers have created an algorithm that slashes the calculations necessary to prepare and customize data for quantum computing.

For PNNL’s Jonathan Evarts, Hope Lackey, and Erik Reinhart, this partnership with WSU opened doors and provided opportunities for their scientific careers to flourish.

By combining computational modeling with experimental research, scientists identified a promising composition that reduces the need for a critical material in an alloy that can withstand extreme environments.

A new generation of microelectronics research begins at PNNL.

Calculating quantum chemistry quickly allows scientists to refine their understanding of complex chemical systems.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

The speed and agility of cloud computing opens doors to completing advanced computational chemistry workflows in days instead of months.

Researchers discussed this topic at the 2024 Analog Computing for Science Workshop co-led by Antonino Tumeo.

PNNL researchers will pursue both fundamental and applied projects with this support from the Department of Energy