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

ChemReasoner combines decades of chemistry knowledge with large language models to propose strategies for effective new catalysts.

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.

PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.

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.

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.