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.

Stakeholders convened at PNNL to build a shared understanding of energy storage siting, permitting, safety, and local engagement.

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

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

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

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.

Through the Air Force Education with Industry program, PNNL is forging powerful connections between research, leadership, and industry.

PNNL cyber defenders are using the Laboratory’s own artificial intelligence research to recognize and address threats quickly.

Margaret Cheung elected to premier scientific society

Custom AI research assistant allows users to ask questions and get answers from hundreds of wildfire mitigation plans.

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

PNNL's Building Energy Model AI is an open-source bot that can help energy modelers save time and money.

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.