A study by researchers at PNNL assessed the feasibility of using strontium isotope ratios and an existing machine learning–based model to predict and verify a product’s source—in this case, honey.

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

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.

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.

Big energy storage science is brewing at GSL just one year after its groundbreaking.

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

The Low-cost Earth-abundant Na-ion Storage consortium is a major effort to create superior, no-compromise batteries that replace lithium with inexpensive, domestically abundant sodium and use few—if any—critical materials.

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.

Experiments focus on catalysts for off-road vehicles that optimize the use of critical minerals while lasting longer and costing less.

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.

Two new publications provide emergency response agencies with critical insights into commercially available unmanned ground vehicles used for hazardous materials response.

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

Jonathan Barr, senior systems engineer at PNNL, was recently invited to co-present on a panel at the Texas Department of Emergency Management Annual Conference.

Matt Fayette, a materials scientist, is testing a new method to extend battery life for grid storage by circulating the electrolyte.

PNNL has created and licensed a system that sniffs out trace levels of fentanyl, other drugs and explosives through the air.