PNNL and Argonne researchers developed and tested a chemical process that successfully captures radioactive byproducts from used nuclear fuel so they could be sent to advanced reactors for destruction while also producing electrical power.
Global climate change is often at the forefront of national and international discussions and controversies, yet many details of the specific contributing factors are poorly understood.
Scientists at PNNL are bringing artificial intelligence into the quest to see whether computers can help humans sift through a sea of experimental data.
A gathering of international experts in Portland, Oregon, explored the future of electron microscopy and surfaced potential solutions in areas including new instrument designs, high-speed detectors, and data analytics capabilities.
A multi-institute team develops an imaging method that reveals how uranium dioxide (UO2) reacts with air. This could improve nuclear fuel development and opens a new domain for imaging the group of radioactive elements known as actinides.
More than 350 people from scientific institutions, education and the private sector gathered at the PNNL campus July 30 for the IEEE Women in Engineering International Leadership Summit.
PNNL Laboratory Director Steve Ashby attended an event marking the 20th anniversary of the Department of Energy’s National Nuclear Security Administration Nuclear Smuggling Detection and Deterrence program.
Researchers apply numerical simulations to understand more about a sturdy material and how its basic structure responds to and resists radiation. The outcomes could help guide development of the resilient materials of the future.
PNNL scientists have taken one of the most in-depth looks ever at the riot of protein activity that underlies colon cancer and have identified potential new molecular targets to try to stop the disease.
It’s hot in there! PNNL researchers take a close, but nonradioactive, look at metal particle formation in a nuclear fuel surrogate material. What they found will help fill knowledge gaps and could lead to better nuclear fuel designs.
Scientists created a fast-track tutorial that equips a neural network to tackle drug discovery and other applications where there's a shortage of precisely labeled chemical data.
Researchers used novel methods to safely create and analyze plutonium samples. The approaches could prove influential in future studies of the radioactive material, benefitting research in legacy, national security and nuclear fuels.
