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.

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.

By combining computational modeling with experimental research, scientists identified a promising composition that reduces the need for a critical material in an alloy that can withstand extreme environments.

How to keep stray radiation from “shorting” superconducting qubits; a pair of studies shows where ionizing radiation is lurking and how to banish it.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

A launch from Cape Canaveral early today carried a PNNL experiment to space so scientists can learn more about radiation far above Earth.

Senior Advisor Isabella van Rooyen shares her journey from child to internationally recognized scientist in nuclear materials and manufacturing.

Researchers designed ultra-low radiation cables to reduce background noise for highly sensitive neutrino and dark matter detectors.

PNNL’s Richard Saldanha will lead a new project to benchmark and validate models of cosmic ray exposure

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

Physicist Emily Mace will share her science journey and an interactive presentation about her current research with middle school and high school students from across the country at the National Science Bowl.

Focused research studies of advanced algorithms and materials are setting the stage for the next generation of quantum computers.

Rotational Hammer Riveting, developed by PNNL, joins dissimilar materials quickly without preheating rivets. The friction-based riveting enables use of lightweight magnesium rivets and also works on aluminum and speeds manufacturing.

PNNL provided ultra-low measurements of argon-39 to date groundwater as part of a collaborative study of the aquifer in California’s San Joaquin Valley. PNNL is one of only a few laboratories worldwide with this capability.

Ultra-trace radiation detection technique sets new global standard for measuring the nearly immeasurable.