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.

Machine learning techniques are accelerating the development of stronger alloys for power plants, which will yield efficiency, cost, and decarbonization benefits.

PNNL is lending analytics expertise to a new first-of-its-kind electric-vehicle carsharing program being launched in Hood River, Oregon.

PNNL’s infrared pulsed heating technique reveals supercooled water’s weird behavior; opens door to other fluid studies at new Energy Sciences Center.

PNNL is developing the Digital Twins for Hydropower framework to help the industry to affordably modernize the aging hydropower fleet.

In the face of the COVID-19 pandemic, PNNL pivoted to online learning approaches to conduct critical national security training across the globe.

PNNL and four other national laboratories executed the Hydropower Value Study to examine hydropower operations in different regions of the United States.

New quantum chemistry pipeline uses thermodynamic calculations to help predict changes in cell metabolism for engineered systems.

PNNL researchers are using explainable artificial intelligence to develop new ways to understand and interpret data for national security.

Study says planners need to account for climate impacts on renewable energy during capacity development planning to fully understand investment implications to the power sector.

High school students from across Washington State competed in the Pacific Northwest Regional Science Bowl, hosted online by PNNL, for a chance to advance to the national competition in May.

Explainable artificial intelligence—understanding and explaining the reasoning behind AI decisions—is a necessity for national security.

PNNL highlights four researchers whose joint appointments are creating new and diverse opportunities for expanding knowledge and scientific impact across institutions.

Explainable AI helps scientists understand and untangle the threads of information that the system uses to make choices or recommendations.

As the COVID-19 pandemic continues, PNNL is offering support to its neighbors in the Mid-Columbia region and across Washington State.

PNNL physicist Jan Strube is defining experimental requirements to track high-energy particles at the proposed International Linear Collider.

Genetic and integrated multi-omic details of glioblastoma could one day inform new therapies.

New approach allows nonexperts to optimize control of a building's energy systems without adding computing power or proprietary software.

PNNL scientists joined international leaders in artificial intelligence research to discuss the latest advances, opportunities, and challenges for neural information processing—the foundation for AI.

PNNL has published a report that sets the foundation for modeling gaps and technical challenges in optimizing hydropower operations for both energy production and water management.