A PNNL study that evaluated the use of friction stir technology on stainless steel has shown that the steel resists erosion more than three times that of its unprocessed counterpart.

PNNL has developed a technology to manufacture rods and tubes directly from high-performance aluminum alloy powder—in just one single step.

Researchers at PNNL are applying deep learning techniques to learn more about neutrinos, part of a worldwide network of researchers trying to understand one of the universe’s most elusive particles.

Patricia Huestis, a collaborator in the Interfacial Dynamics in Radioactive Environments and Materials (IDREAM) Energy Frontier Research Center, has been awarded the DOE Office of Science Graduate Student Research (SCGSR) award.

Keerti S. Kappagantula, a scientist in PNNL’s Energy Processes and Materials Division, was featured in ASM International’s Women in Engineering Series.

A new technology that offers a novel way to manufacture extrusions with unprecedented improvements in material properties recently received a U.S. patent.

The feature article shines a spotlight on the Energy Frontier Research Center led by PNNL.

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.

PNNL scientists today unveiled an updated tool designed to help stakeholders assess the nation's preparedness for biological-based dangers, also known as biothreats.

Researchers at PNNL used key metrics to develop visualizations that show how the combined effects of climate change on hydropower and load influence the frequency, duration, and severity of power shortfalls.

PNNL is advancing scientific frontiers and addressing challenges in energy, the environment and national security. So, in no particular order, here are PNNL's top 10 research accomplishments of 2018

Plug and Play DER Challenge seeks to enable distributed energy technologies to integrate, connect and operate in harmony on the power grid.

Scientists are exploring the use of deep neural network to interpret highly technical data related to national security, the environment and the cosmos.

New technique developed by PNNL successfully joins thicker aluminum alloys to steel