Complex metal alloys enter a new era of predictive design for aerospace and other high-temperature applications.

The Department of Energy Office of Nuclear Energy acting assistant secretary makes his first visit to a national laboratory in his new role, touring PNNL's Radiochemical Processing Laboratory.

PNNL researchers review ceramic-metal composite technology for immobilizing radioactive wastes from nuclear reactors, including advanced reactors.

The 2024 Jack Simons Award honor recognizes Li for his expertise in integrating chemistry with computing for fundamental science research.

IDREAM scientists capture electronic response to ionization.

A breakthrough in electron microscopy based on deep learning can automatically visualize and identify areas of interest, helping to speed advances in materials science.

IDREAM research shows the size of cations in highly concentrated nitrite solutions affects the production of radicals.

PNNL research exploring tungsten heavy alloys for use in advanced nuclear fusion reactors makes Scientific Reports Top 100 Collection.

A new AI model developed at PNNL can identify patterns in electron microscope images of materials without requiring human intervention, allowing for more accurate and consistent materials science.

Senior Advisor Isabella van Rooyen shares her journey from child to internationally recognized scientist in nuclear materials and manufacturing.

PNNL researchers use chemometric analysis to model chemistry in molten salt.

Scientists stop the motion of atoms to watch electrons move in liquid water.

Differences in water interactions lead to two gibbsite dissolution pathways modulated by solution acidity.

Visual Sample Plan, a free software tool developed at PNNL that boosts statistics-based planning, has been recognized with a 2024 Federal Laboratory Consortium Award.

Irradiation in a sodium hydroxide solution increases the dissolution rate and particle roughness of gibbsite compared to dry irradiation.

Resolving how nanoparticles come together is important for industry and environmental remediation. New work predicts nanoparticle aggregation behavior across a wide range of scales for the first time.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

PNNL chemical engineer Reid Peterson helped develop the process to pretreat Hanford Site tank waste by removing cesium-137.

NRC Chair Christopher Hanson tours the nondestructive examination laboratories and learns more about PNNL’s broad support to the NRC mission.