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.

di Vacri’s expertise in low-background detection earned her a place on the Executive Board of the Coordinating Panel for Advanced Detectors.

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.

In the search for rare physics events, extremely pure materials are essential. A partnership between PNNL and Ultramet has led to tungsten with low contamination from other elements.

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.

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

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.

Scientists are studying tiny subatomic particles that pass through humans and possess clues about the origins of the universe.

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

PNNL is honoring its postdoctoral researchers as part of the fourteenth annual National Postdoc Appreciation Week with seven profiles of postdocs from around the Laboratory.

Neutrino mass, a crucial piece of many unresolved physics puzzles, may one day be revealed through a novel measurement system that has just proven its mettle: Cyclotron Radiation Emission Spectroscopy.

IDREAM researchers assess the potential of photon-in/photon-out XFEL techniques to explore early time reaction steps and ultimately improve nuclear waste processing strategies.

Brent VanDevender is an experimental nuclear physicist and the program manager for nuclear physics research at PNNL.

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.

The Washington State Academy of Sciences consists of more than 300 elected members who are nationally recognized for their scientific and technical expertise.