Emilie Purvine, a chief data scientist at PNNL, was elected as a council member at large of the American Mathematical Society.

Summarizing the state of designed protein hybrid materials, researchers celebrate both the 50th anniversary of the MRS Bulletin and the 2025 Fred Kavli Distinguished Lecturers in Materials Science, Jim De Yoreo and David Baker.

Mystery of how important aluminum minerals form and dissolve solved with materials science and advanced imaging studies.

Researcher and graduate student Renyu Zheng selected for premier research recognition from the University of Washington Chemical Engineering Department.

Specially designed histidine-containing peptoids mimic carbonic anhydrase to accelerate calcite step growth.

An award-winning computing method called poly-streaming accelerates the analysis of massive datasets while using limited memory.

PNNL brings its expertise to the space domain by joining an organization that facilitates collaboration across the global space industry.

Ice crystals are surprisingly tolerant of defects in their structure. The findings come from the first-ever molecular-resolution observations of nanoscale samples of ice frozen from liquid water.

Imaging ice microstructures formed by water freezing with atomic resolution for the first time.

This achievement earned DIMPLES a Best Paper award at the ACM International Conference on Supercomputing 2025.

As Laboratory Director Steve Ashby pens his last monthly column, he highlights PNNL’s accomplishments with pride and gratitude.

Tailored assemblies mimic natural enzyme activity with significantly higher stability.

In high-entropy oxides, chromium tends to segregate during growth due to oxidation-induced migration of smaller, high-valence cations.

Three research teams led by PNNL organizers achieve journal publications following the Mathematics Research Communities program.

Researchers developed a way to precisely control dopant structures and locations in carbon-based materials.

Through an unprecedented collaboration with Idaho, Savannah River, and Argonne national laboratories, the Athena Project has built a network of nearly 150 scientists.

PNNL showcased its expertise in AI, machine learning, and related domains at the International Conference on Machine Learning.

Researchers have begun a series of experiments that could bring about more energy for grid, thanks to a special delivery of 11 "high burnup" rods.

Scientists have tapped AI and powerful computing to speed up how quickly officials are able to learn important details about nuclear events.

Expanding the nation’s largest wind power plant time series database; helping grid planners navigate a resilient energy future with better data.