PNNL has developed a next-generation electrical resistivity tomography system for DOE that uses E4D software and AI-enhanced modeling to produce real-time subsurface images that help guide environmental remediation decisions.

Secretary Wright visited PNNL's campus in Richland, Washington, late last year to meet with innovators in chemistry, biology, computing, and more.

Distributed science is thriving at PNNL, where scientists share data and collaborate with researchers around the world to increase the impact of the work.

A closed-loop workflow brings together digital and physical frameworks to advance high-throughput experimentation on redox-active molecules in flow batteries.

Shear Assisted Processing and Extrusion (ShAPE) imparts significantly more deformation compared to conventional extrusion. The latest ShAPE system at PNNL, ShAPEshifter, is a purpose-built machine designed for maximum configurability.

More than 25,000 participants from industry, government, academia, and the public attended the event.

Klickitat Valley Health's fuel cell and microgrid project boosts rural healthcare, enhancing energy resilience and sustainability for social equity.

Data from SOSAT web tool informs site selection and management for the subsurface injection of captured carbon dioxide.

To improve our ability to “see” into the subsurface, scientists need to understand how different mineral surfaces respond to electrical signals at the molecular scale.

PNNL researchers led a collaborative effort to showcase the most up-to-date, innovative, commercial cement and concrete technologies.

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.