Amine functionalized graphene oxide yields laminates with an enhanced capacity to adsorb rare earth elements, improved water transport, and greater stability for effective membrane-based separation of critical minerals.

Developed a method for selectively anchoring diverse divalent metal cations in zeolites, important for precise control over catalytic materials.

Replacing commercial acid with acidic waste enables researchers to improve nickel extraction efficiency, lower projected costs, and improve process economics.

A recent article highlighted a PNNL report focused on post-quantum cryptography and electric vehicle charging infrastructure.

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.

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.

Soil mineral preferentially incorporates rare earth elements based on size, with implications for critical mineral extraction.

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.

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

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.

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.

This study presents an automated method to detect and classify open- and closed-cell mesoscale cellular convection (MCC) using long-term ground-based radar observations.

Ampcera has an exclusive licensing agreement with PNNL to commercially develop and license a new battery material for applications such as vehicles and personal electronics.

PNNL's new energy storage facility now houses the Lab's vehicle battery research programs, which have more lab space and a slew of new capabilities.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

Models have identified a new source of anthropogenic emissions driving the observed weakening of the Atlantic Meridional Overturning Circulation.