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.

From vehicles and airplanes to solid-phase processing of metals—how Curt Lavender and his team at PNNL solve industry problems with practical ingenuity.

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.

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.

Lauren Charles, a chief data scientist at PNNL, showcased the vital research coming out of her program at The National Academies Forum workshop in Washington, D.C., January 15–16, 2025.

PNNL biodefense experts seek to identify, understand and mitigate the risks of biological pathogens—whether naturally occurring or intentionally created—so steps can be taken to prepare and respond.

Researchers will explore climate, pathogens and energy-efficient microelectronics using 3 million node hours on the nation’s supercomputers.

PNNL’s patented Shear Assisted Processing and Extrusion (ShAPE™) technique is an advanced manufacturing technology that enables better-performing materials and components while offering opportunities to reduce costs and energy consumption.

Scott Whalen, a chief scientist in the Applied Materials and Manufacturing group at PNNL, has been named 2023 PNNL Inventor of the Year

Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.

Beyond melting ice and higher temperatures: On Earth Day, scientists consider how climate change will affect national security.

The next-generation ShAPE machine has arrived at PNNL, where it will help prove the mettle of the ShAPE extrusion technique. ShAPE 2 is designed to allow researchers to produce larger, more complex extrusions.

The Department of Energy’s Vehicle Technologies Office recently issued two awards to researchers at PNNL for their contributions to areas that are crucial for the expansion of electric vehicles.

The PNNL-patented ShAPE™ manufacturing process produces high-strength aluminum vehicle parts that lower costs and are more environmentally friendly.

PNNL senior materials scientist Keerti Kappagantula has been named to the 2023 Nominating Committee of ASM International.

Microbes that were previously frozen in soils are becoming more active. This study demonstrates the diverse RNA viral communities found in thawed permafrost.