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.

Recognizing visionary scientists for exceptional research, leadership, and impact at PNNL.

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

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

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.

PNNL's E-COMP initiative is helping unleash American energy innovation with advanced theories, models, and software tools to better operate power systems that rely heavily on high-speed power electronic control.

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.

PNNL’s experts in electrification advised ports how to modernize the use of energy resources at the Port of Anacortes. Now they will help do the same with several others.

A PNNL team has developed an energy- and chemical-efficient method of separating valuable critical minerals from dissolved solutions of rare earth element magnets.

The ARPA-E Energy Innovation Summit brings together researchers, industry leaders, entrepreneurs, and investors to showcase the latest technologies shaping tomorrow’s energy landscape. This year, eight projects led by PNNL were featured.

Surface manganese mining from nodules in South Dakota is now possible with a new scalable selective precipitation process.

Three PNNL technologies have been declared winners of 2025 Federal Laboratory Consortium Awards, named for a program that recognizes federal laboratories and their industry partners for outstanding technology transfer achievements.

Cobalt substitution for magnesium in a model mafic mineral dramatically slows reaction with carbon dioxide to form a cobalt-doped carbonate.

PNNL teamed up with multiple agencies to install a battery energy storage system at a South Dakota Air Force base.

Precipitation with sodium hydroxide in a flow-gel device enables the rapid extraction of magnesium from seawater in a new scalable process.

The atomic-level distribution of nickel and cobalt in forsterite depends on the concentration of the different elements.