Early career researchers recognized with Team Science Award by the Department of Energy for presentation highlighting the collaborative science performed by IDREAM.

IDREAM researchers uncovered how dimeric complexes control how aluminum hydroxide minerals dissolve.

PNNL researchers are opening up a new front in the fight to stop viral pathogens, protecting people against multiple viruses.

Capturing protein structural changes in host cells exposes vulnerabilities exploited by viruses to hijack cellular machinery.

From developing new energy storage materials to revealing patterns of Earth’s complex systems, studies led by PNNL researchers are recognized for their innovation and influence.

Researchers are uncovering the secrets of a fast-acting molecular messaging network that helps determine how the genetic code plays out.

From producing radioisotope generators to recovering source materials, researchers are meeting a growing need for medical radioisotopes.

The ability of a storm-resolving weather model to predict the growth of storms over central Argentina was evaluated with data from the Clouds, Aerosols, and Complex Terrain Interactions (CACTI) field campaign in central Argentina.

PermitAI’s newly released dataset, NEPATEC 2.0, captures and curates environmental review data for faster, better federal permitting.

PNNL researchers continue to deliver high-quality, high-impact research on radioactive waste and nuclear materials management, earning “Papers of Note” and “Superior Paper” awards.

Researchers have developed the first coastal transport model for microplastics to understand how particles move in waterways and coastal currents.

The Department of Energy Art of Science contest entry focuses on the extraordinary universe of chemical bond making and breaking under irradiation.

Trace amounts of iron and chromium can incorporate into gibbsite, affecting how the mineral dissolves.

New electees represent research in genomics, grid resilience, coastal ecology, and more.

Researchers from PNNL and Parallel Works, Inc., applied machine learning methods to predict how much oxygen and nutrients are used by microorganisms in river sediments.

PNNL researchers showcased subsurface sampling and remediation expertise at the 2025 Federal Remediation Technologies Roundtable.

Lakes are important sentinels of climate change and contribute significantly to the emissions of the second most important greenhouse gas—methane.

The rate of conversion of cloud droplets to precipitation, known as the autoconversion rate, remains a major source of uncertainty in characterizing aerosol’s cloud lifetime effects and precipitation in global and regional models.

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

To assess the impact of observation period and gauge location, model parameters were learned on scenarios using different chunks of streamflow observations.