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.

The Generator Scorecard, developed by PNNL in partnership with BPA, automates generator evaluations, reducing engineering workloads and improving grid reliability.

EGRASS wins in the software/services category and is awarded a gold medal as special recognition in corporate social responsibility.

The National Transmission Planning Study presents several transmission expansion scenarios that would reliably support the growing demand for energy across the nation.

Staff at PNNL recently traveled to Cyprus to facilitate a multilateral workshop on chemical forensics investigations hosted by the U.S. Department of State, Office of Weapons of Mass Destruction Terrorism.

Three PNNL technologies have been named 2024 R&D 100 Award winners.

PNNL welcomed United Kingdom researcher for a six-week hands-on research exchange to develop nuclear forensic techniques.

Capstone engineering projects deliver equipment to improve accuracy of chemistry lab elutions and enhance training to safeguard critical infrastructure.

PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.

ChatGrid™ is a practical application of the Department of Energy’s exascale computing efforts and offers a new experience in easy, intuitive, and interactive data interaction.

Results of the PR100 study outline near- and short-term strategies for Puerto Rico to achieve a renewable power grid by 2050.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.

Glenn Fugate was selected to serve on the American Chemical Society's Science Committee.