Researchers at PNNL have developed an interpretable, lightweight AI model that can easily predict weld microstructure features using only basic machine sensor inputs.

Secretary Wright visited PNNL's campus in Richland, Washington, late last year to meet with innovators in chemistry, biology, computing, and more.

This summer, PNNL hosted the inaugural “As Conductive As Copper” (AC2.0) workshop, fostering a collaborative conversation on the future of the U.S. copper supply chain.

More than 25,000 participants from industry, government, academia, and the public attended the event.

University of Washington Professor David Baker won the 2024 Nobel Prize in Chemistry for computational protein design.

Pacific Northwest National Laboratory scientists discussed their materials research at Accelerate’24.

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

PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.