Understanding the risk of compound energy droughts—times when the sun doesn’t shine and the wind doesn’t blow—will help grid planners understand where energy storage is needed most.

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.

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.

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

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.

Floating offshore wind farms could potentially triple the Pacific Northwest's wind power capacity while offsetting billions of dollars in costs for utilities, ratepayers, insurance companies, and others.

Developed with community input, the new Hydropower Vision Roadmap lays out a path to achieve a shared vison for modern hydropower by 2050.

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.