The PNNL-developed UF6 Gas Enrichment Sensor (UGES) prototype is the next generation of a previous enrichment monitoring device—namely the Online Enrichment Monitor. UGES will increase the accuracy of uranium measurements.

Delivering excellence in power systems and electric grid advancement earns two PNNLers the association’s top distinction.

Researchers at PNNL share a research- and practitioner-informed approach to assess the threat landscape, elicit and integrate feedback into solutions, and ultimately share outcomes with the emergency response and public safety community.

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.

PNNL brings its expertise to the space domain by joining an organization that facilitates collaboration across the global space industry.

As Laboratory Director Steve Ashby pens his last monthly column, he highlights PNNL’s accomplishments with pride and gratitude.

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.

Through an unprecedented collaboration with Idaho, Savannah River, and Argonne national laboratories, the Athena Project has built a network of nearly 150 scientists.

Researchers have begun a series of experiments that could bring about more energy for grid, thanks to a special delivery of 11 "high burnup" rods.

Aaron Luttman and Jonathan Forman represented PNNL at the high-profile "Risk and Reduction Science and Policy Forum" organized by Johns Hopkins University and supported by the Defense Threat Reduction Agency.

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.

Two new publications provide emergency response agencies with critical insights into commercially available unmanned ground vehicles used for hazardous materials response.

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.