A breakthrough at PNNL could free friction stir from current constraints—and open the door for increased use of the advanced manufacturing technique on commercial assembly lines.

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.

Led by interns from multiple DOE programs, a newly expanded dataset allows researchers to use easy-to-obtain measurements to determine the elemental composition of a promising carbon storage mineral.

A multi-institutional team of researchers systematically compared extraction techniques for characterizing plant litter composition that relies on organic matter extraction.

New methodology can evaluate the potential for carbon storage and critical mineral recovery in undercharacterized geological settings.

A new database allows researchers to connect lattice parameters and composition in olivine.

Research identifies the mechanisms through which peptoids affect ions in solution and a mineral surface, increasing the rate of carbonate crystal growth.

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

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

PNNL undergraduate intern Madeline Bartels leads research to verify and quantify carbon mineralization at an unprecedented small scale.

Frederick Day-Lewis, Lab Fellow and chief geophysicist at PNNL, was named the 2024 recipient of the Geological Society of America Public Service Award.

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

PNNL research unlocks key findings needed for potential commercial deployment of carbon mineralization technology.

Department of Energy’s Advanced Research Projects Agency-Energy selects PNNL project to help accelerate the development of marine carbon dioxide removal technologies.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.

PNNL’s software tool brings together artificial intelligence and satellite imagery to help responders assess damage and take action.

A suite of experiments provide insight into how diopside reacts with carbon dioxide to form stable carbonate species.

PNNL-Sequim scientists will spend the next year testing a new technology that could allow the ocean to soak up more carbon dioxide without contributing to ocean acidification.

Recovery Simulator and Analysis tool further strengthens PNNL’s short-term resilience planning efforts for Puerto Rico.

Newly developed models can help rapidly optimize systems to meet the need for rapidly deployable commercial carbon capture.