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.

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.

Micron and PNNL co-design the Crete computer system, delivering a new memory architecture for data-intensive scientific computing and AI applications.

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

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.

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

PNNL Program Development Office Director Karl Mueller explains how the TEC4 project seeks to make advanced chemical computations accessible to all.

CACTUS provides AI-powered cheminformatics for autonomous science.

University of Washington Professor David Baker won the 2024 Nobel Prize in Chemistry for computational protein design.

The speed and agility of cloud computing opens doors to completing advanced computational chemistry workflows in days instead of months.

ChemReasoner combines decades of chemistry knowledge with large language models to propose strategies for effective new catalysts.

Researchers will explore climate, pathogens and energy-efficient microelectronics using 3 million node hours on the nation’s supercomputers.

New research informs the development of foundational models for computational chemistry through hardware-software co-design.

A team of scientists at PNNL developed new computational models to predict the behavior of these impurities and reduce the expense and risk related to actinide metal production.

PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

Computational chemistry libraries from NWChem, NWChemEX, SPEC, and more are now available on Azure Quantum Elements.

Advances in understanding the nature of the chemical bond are featured in this special issue of The Journal of Chemical Physics.

Fundamental research conducted at the $90-million research facility will help the nation meet its clean energy goals.