PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

A team of scientists at PNNL developed new computational models to predict the behavior of these impurities and reduce the expense and risk related to actinide metal production.

More than a dozen PNNL scientists have been named among the world’s most influential researchers on Clarivate’s 2023 Highly Cited Researchers List.

Resolving how nanoparticles come together is important for industry and environmental remediation. New work predicts nanoparticle aggregation behavior across a wide range of scales for the first time.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.

PNNL chemical engineer Reid Peterson helped develop the process to pretreat Hanford Site tank waste by removing cesium-137.

PNNL’s DataLife tool analyzes and identifies bottlenecks in scientific workflows.

A novel electrode functionalization strategy enables efficient removal of toxic heavy metals from wastewater.

1-propanol converts from a monomer into a trimer at aluminum sites within zeolite pores.

The use of disciplines in pure mathematics can increase the reliability and explainability of machine learning models that “transcend human intuition,” according to PNNL scientists.

NRC Chair Christopher Hanson tours the nondestructive examination laboratories and learns more about PNNL’s broad support to the NRC mission.

Researchers designed a new, highly efficient, stable redox-active material from neutral red dye that can efficiently capture CO2 from air.

Leaders from the DOE Office of Energy Efficiency and Renewable Energy visited PNNL October 19–20 for a firsthand look at capabilities and research progress.

Tumeo will lead the ChemComp project, which was awarded for Exploratory Research in Extreme Scale Science

Converting seawater into hydrogen fuel using electrochemistry offers a renewable energy future for Guam.

PNNL researchers are key contributors to GAO report

Robert Rallo from Pacific Northwest National Laboratory will direct a machine learning thrust for a new Department of Energy-funded project led by SLAC National Accelerator Laboratory.

Lauren Charles has been named a scientist and engineer level 5 in the national security domain.

Lynn Wood has been named a scientist and engineer level 5 in the national security domain.

Mike Giardinelli has been named a scientist and engineer level 5 in the national security domain.