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

Visit featured information exchange and tours of PNNL work and facilities that relate to the work of the International Atomic Energy Agency.

The Deep Vadose Zone program leads a treatability study for subsurface remediation of the Hanford Site’s Central Plateau.

PNNL’s Center for the Remediation of Complex Sites convened attendees from around the world to discuss challenges associated with environmental contamination.

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

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.

Scientists at PNNL have published a new article that focuses on understanding the composition, dynamics, and deployment of beneficial soil microbiomes to get the most out of soil.

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.

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.

A poem inspired by radioactive tank waste—“Can a Scientist Dream it Alone?”—was awarded first place in the Department of Energy’s Poetry of Science Art Contest.

Researchers unveil user-friendly software to keep complex projects on budget and on schedule.

PNNL chemists investigate the performance of ion exchange resins for subsurface remediation of uranium, technetium, and chromium.

DOE Basic Energy Sciences 2023 “Poetry of Science Art Contest” aims to educate and inspire; voting for the People’s Choice Award closes September 15.

Bradley Crowell with the U.S. Nuclear Regulatory Commission sees advanced materials integrity, radiological measurement, and environmental capabilities on his first visit to PNNL.

The Rapid Assessment of Platform Technologies to Expedite Response project aims to prepare against future pandemics.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

To overcome high-performance computing bottlenecks, a research team at PNNL proposed using graph theory, a mathematical field that explores relationships and connections between a number, or cluster, of points in a space.

Methods review suggests ways to use artificial intelligence and machine learning to handle missing data when integrating two or more omics approaches.