David Donnelly, an international compliance analyst at PNNL, recently served on a team of experts that completed the International Atomic Energy Agency’s first International Physical Protection Advisory Service mission in Kenya.

Scientists are tapping earthquake data to develop a new AI foundation model called SeisModal.

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.

Peter Heine, senior advisor in the Strategic Threat Analysis group at PNNL, recently travelled to Brussels, Belgium, to support the World Customs Organization's Operation Stingray.

A team of researchers at PNNL has received the 2025 National Nuclear Security Administration CIO Award for developing an innovative solution to enhance secure communications.

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.

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.

Directionally biased electrostatic interactions are the key to significantly tuning the reduction potential of iron/sulfur clusters.

For PNNL’s Jonathan Evarts, Hope Lackey, and Erik Reinhart, this partnership with WSU opened doors and provided opportunities for their scientific careers to flourish.

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.

Staff at PNNL recently visited the University of Texas at San Antonio to deliver lectures on international law, arms control, and nuclear nonproliferation during Nuclear Policy Week.

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

Early life exposure to polycyclic aromatic hydrocarbons (PAHs), found in smoke, has been linked to developmental problems. To study the impacts of these pollutants, PAH metabolism in infants and adults were compared.