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.

PermitAI’s newly released dataset, NEPATEC 2.0, captures and curates environmental review data for faster, better federal permitting.

PNNL chemical engineer Mariefel Olarte shares passion for mentoring students and the next-generation workforce.

A new generation of microelectronics research begins at PNNL.

How to keep stray radiation from “shorting” superconducting qubits; a pair of studies shows where ionizing radiation is lurking and how to banish it.

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.

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.