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

Dušan Veličković, a PNNL mass spectrometry imaging scientist received a $2.1 million grant to develop techniques to understand how changes in carbohydrate structure affect human health.

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 has created and licensed a system that sniffs out trace levels of fentanyl, other drugs and explosives through the air.

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 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.

Scientists are developing ways to detect previously unseen forms of fentanyl as well as other synthetic opioids known as nitazenes.

A cross-institutional team of scientists developed PeakQC, a new software tool for automated quality control of mass spectrometry data.

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.

Ljiljana Paša-Tolić, a PNNL fellow, is the recipient of the 2024 International Mass Spectrometry Foundation’s Jochen Franzen Award. 

Scientists have developed a way to detect tiny amounts of hard-to-detect explosives more than eight feet away.