Mystery of how important aluminum minerals form and dissolve solved with materials science and advanced imaging studies.

A potential quantum advantage for fluid dynamics simulations from molecular to atmospheric scales with a new formula for success.

Three PNNL researchers will receive five continuous years of funding for projects through highly competitive DOE Early Career Research Program awards.

Three PNNL technologies have been named 2024 R&D 100 Award winners.

Neeraj Kumar discusses how AI can transform scientific research at the Platform for Advanced Scientific Computing Conference and Trillion Parameter Consortium European Workshop.

Researchers will explore climate, pathogens and energy-efficient microelectronics using 3 million node hours on the nation’s supercomputers.

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

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

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.