An AI program called AtomAI helped PNNL researchers reveal key design principles for protein interfaces with mineral surfaces.

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

Ice crystals are surprisingly tolerant of defects in their structure. The findings come from the first-ever molecular-resolution observations of nanoscale samples of ice frozen from liquid water.

A new generation of microelectronics research begins at PNNL.

Ultra-thin layers of silk deposited on graphene in perfect alignment represent a key advance for the control needed in microelectronics and advanced neural network development.

Bylaska and team will aim to make computational design of functional materials more targeted, impactful, and user friendly through this award.

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

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.

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.