PNNL chemist and AI scientist Nancy Washton invited to present on AI literacy at National Science Bowl.

Funded by DOE’s Office of Electricity, the GSL at PNNL has been recognized by BCI for accelerating the deployment of grid-ready storage solutions.

Formal mathematics both reveals what’s inside the black box of AI algorithms and pushes the boundary of what’s possible within math as a discipline.

Backed by $75,000 in Department of Energy funding from the Office of Electricity, a PNNL researcher works to refine solid-state sodium batteries for the grid.

PNNL's “co-scientist” serves as a one-stop AI shop for accelerating scientific discovery. By leveraging AI agents, researchers can explore scientific databases, conduct analyses and request step-by-step plans for testing their hypotheses.

PNNL is hosting a scientific conference focused directly on understanding and predicting the collection of an organism’s traits.

Chemist Wendy Shaw, a nationally recognized scientific leader, has been chosen to serve as the associate laboratory director for PNNL's Physical and Computational Sciences Directorate.

Scott Tingey will steward PNNL’s 10-year, $1.2-billion campus development and modernization plan.

PNNL’s Yong Wang has been elected to the National Academy of Engineering and will be inducted in October.

Researchers can now quantify uncertainty in trained AI models aimed at solving difficult chemistry, biology and materials science problems.

Chief Digital Officer Brian Abrahamson earns industry honor with CIO Hall of Fame distinction.

Researchers have created an algorithm that slashes the calculations necessary to prepare and customize data for quantum computing.

Researchers discovered a new way to more efficiently and affordably create nickel-rich battery materials.

Circadian rhythms of blue-green microbes offer new window into predictive phenomics—how to predict and control the traits of an organism.

Surface manganese mining from nodules in South Dakota is now possible with a new scalable selective precipitation process.

Researchers at PNNL are pursuing new approaches to understand, predict and control the phenome—the collection of biological traits within an organism shaped by its genes and interactions with the environment.

Machine learning and autonomous experimentation are poised to revolutionize how scientists grow very thin films on surfaces, important for technologies like microelectronics and quantum computing.

Chemist Zheming Wang is the newest AAAS Fellow, joining the ranks of astronaut Mae Jemison, and Steven Chu, 1997 Nobel laureate in physics who served as the 12th U.S. Secretary of Energy.

Over the next four years, PNNL and University of Arizona will develop open-source computational tools to better identify and characterize the viruses associated with the human microbiome.