Award-winning research advances AI applications for environmental cleanup.

New software enables the study of nuclear quantum effects in large, condensed phase systems up to 10× faster than traditional methods.

PNNL’s nondestructive evaluation capabilities support advancements in nuclear energy, including research for the U.S. Nuclear Regulatory Commission to preserve the nation’s existing nuclear fleet.

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

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.

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

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.

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

The Hanford Site is now immobilizing radioactive waste in glass: a process known as vitrification. PNNL contributed 60 years of materials science expertise—and is providing operational support—to help the nation meet this cleanup milestone.

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

Nanosize platelets of an aluminum material slide and join in a staggered orientation to form larger crystals.

Early career researchers recognized with Team Science Award by the Department of Energy for presentation highlighting the collaborative science performed by IDREAM.

The Department of Energy, Basic Energy Sciences and Advanced Scientific Computing Research programs will support the partnership’s work on nuclear quantum behavior.

IDREAM researchers uncovered how dimeric complexes control how aluminum hydroxide minerals dissolve.

Scientists provide a guide for the rational application of continuum descriptions of fluid flows based on interfacial chemistry.

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.

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.