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.

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.

Expanding the nation’s largest wind power plant time series database; helping grid planners navigate a resilient energy future with better data.

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.

Engineers at PNNL devised a system that allows radar antennae to maintain stable orientation while mounted on platforms in open water that pitch and roll unpredictably. They were recently invited to participate in DOE's I-Corps program.

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.

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

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

A new report details the potential for floating offshore wind to lower energy costs and enhance the resilience of the nation’s western grid.

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

PNNL's accomplishments in FY 2024 help address the remaining challenges the wind industry faces.

PNNL was well represented at the NAWEA/WindTech 2024 Conference with 13 PNNL experts at the conference sponsored by the North American Wind Energy Academy.

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

Latest Distributed Wind Market Report helps the Department of Energy identify market trends and new opportunities for distributed wind power projects.