High-Velocity Joining is a new joining technology that could reduce energy use and cost for manufacturers.

PNNL’s Robert Rallo and Nathan Hodas speak to students about the future of AI.

Scientists equipped research subjects with wristbands to measure many factors that contribute to their exposome.

A newly published custom collection of glass formulas for nuclear waste vitrification — developed and validated by PNNL over the past three years — was made possible in that timeframe with AI tools, including a PNNL machine learning model.

Scientists are optimizing microbes to harvest critical minerals and produce bioproducts using AI and autonomous lab equipment.

At the summit, PNNL engaged with partners and investors, highlighting seven projects that accelerate the deployment of new energy technologies.

An international research team deployed AI-powered computing to solve important chemical structures for energy applications using NVIDIA hardware.

PNNL has chosen three proven leaders to serve in key roles guiding lab research and operations.

David Wunschel, a chemist and Laboratory Fellow, participated on a panel focused on how emerging technologies are transforming CBRN defense, detection, and response across military and government operations.

Integrating new functions into a genome-scale model enabled researchers to simulate and experimentally validate viral hijacking pathways.

PNNL chemist Sarah Saslow received the ACS Rising Star Award for her research supporting environmental cleanup, including work on legacy waste and subsurface contamination.

A suite of new modeling methods gives researchers better tools to predict molecular behavior inside cavities.

The underlying crystal structure of carbonate surfaces plays a key role in the formation of cobalt mineral structures on these surfaces.

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.

Margaret Cheung elected to premier scientific society.

Replacing commercial acid with acidic waste enables researchers to improve nickel extraction efficiency, lower projected costs, and improve process economics.

A microbial community expresses a phenotype of interest ~20 percent higher than the sum of each member species.

SenseAI and VaporID have been deployed by multiple industry partners.

Automated liquid handling, combined with data analysis and AI, optimizes microbiological growth conditions at PNNL.

Explore the past, present, and future of technological advancements made by scientists at PNNL.