Localized gradients in magnetic fields have long-range effects on the concentration of rare earth ions in solution, facilitating field-driven extraction of critical minerals.

Studying a series of rare earth element compounds revealed differences in their magnetic behavior that will be leveraged for separations.

Mystery of how important aluminum minerals form and dissolve solved with materials science and advanced imaging studies.

Nanosize platelets of an aluminum material slide and join in a staggered orientation to form larger crystals.

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.

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.

Nanoscale domains of magnetically susceptible critical materials encounter enhanced magnetic interactions under external magnetic fields, providing a promising new avenue for separations.

David Heldebrant was selected for the 2025 Distinguished Service Award from the American Chemical Society Division of Energy & Fuels, recognizing his impact to energy and fuels chemistry.

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.

The size of graphene oxide sheets affects the ability of assembled membranes and adsorbents to separate rare earth elements.

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.

Scientists have tapped AI and powerful computing to speed up how quickly officials are able to learn important details about nuclear events.

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

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.

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