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

PNNL researchers learn to control peptoid “handedness,” one key to precision drug delivery and diagnostics.

A nontoxic separation process recovers critical minerals from electronic scrap waste.

As new paradigms in advanced computing take shape, computational chemistry researchers are finding new ways to solve challenging chemistry problems.

The next-generation ShAPE machine has arrived at PNNL, where it will help prove the mettle of the ShAPE extrusion technique. ShAPE 2 is designed to allow researchers to produce larger, more complex extrusions.

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.

Researchers at PNNL have developed a new technique to get a high-resolution look at how—and why—corrosion happens.

PNNL scientists have put forth a new approach to protect the electric grid, creating an approach that sorts and prioritizes cyber threats on the fly.

ChatGrid™ is a practical application of the Department of Energy’s exascale computing efforts and offers a new experience in easy, intuitive, and interactive data interaction.

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.

The convergence of artificial intelligence, cloud, and high-performance computing to accelerate scientific discovery is the focus of a multi-year collaboration between Microsoft and PNNL.

A newly developed, highly conductive copper wire could find applications in the electric grid, as well as in homes and businesses. The finding defies what's been thought about how metals conduct electricity.

PNNL has created the Center for AI @PNNL to coordinate the pioneering research of hundreds of scientists working on a range of projects in artificial intelligence.

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

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

Converting seawater into hydrogen fuel using electrochemistry offers a renewable energy future for Guam.

Rechargeable battery performance could be improved by a new understanding of how batteries work at the molecular level. Researchers at PNNL upend what's known about how rechargeable batteries function.

PNNL is collaborating with Microsoft, Micron and other partners to make computational chemistry broadly available.

From Mexico and Ethiopia to a U.S. national lab, interns are ready to contribute to a sustainable energy future.