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.

Big energy storage science is brewing at GSL just one year after its groundbreaking.

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.

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.

Matt Fayette, a materials scientist, is testing a new method to extend battery life for grid storage by circulating the electrolyte.

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.

Mini flow cell battery provides the first step toward an AI-driven, robotic energy storage discovery laboratory.

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.

From enhancing biofuel crops to setting up automated experiments and improving energy storage—interns at PNNL are making an impact.

The Grid Storage Launchpad dedication event was attended by leaders in grid and transportation energy storage, battery innovation, and industry stakeholders working to transform America’s energy system.

Anderson is one of only 25 women from throughout the world selected to participate in the Epistimi-Women in STEMM Leadership Workshop on “Women in the Energy Sector,” held July 15–19 in Athens, Greece.

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.