PNNL researchers Daniel Deng and Yehia Ibrahim join the 2025 class of National Academy of Inventors Fellows.

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.

ThermalTracker-3D can help streamline permitting, reduce costs, and shorten development time of energy projects.

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.

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.

di Vacri’s expertise in low-background detection earned her a place on the Executive Board of the Coordinating Panel for Advanced Detectors.

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.

In the search for rare physics events, extremely pure materials are essential. A partnership between PNNL and Ultramet has led to tungsten with low contamination from other elements.

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

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.

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

With the launch of a large research barge, PNNL and collaborators took another significant step to improve offshore wind forecasting that will lower risk and cost associated with offshore wind energy development.