PNNL recently led a team effort that secured external accreditation for the Office of Radiological Security Radiological Security Awareness and Response Communications Workshop.

Working with DOE and PNNL, Google has created a new badge that will help consumers find highly skilled home energy specialists.

PNNL researchers will deploy advanced AI systems to study how to best secure the future electric grid.

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.

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.