Argonne’s Rapid Prototyping Laboratory is helping undergraduate and graduate students prepare for future science careers. Their efforts are paving the way for automating lab work with robotics and AI in autonomous discovery.
In an npj Computational Materials paper, scientists report on a Crystal Edge Graph Attention Neural Network able to classify materials across multiple scales (from atomic to mesoscale) and diverse classes (metals, non-metals, zeolites, etc.)
In a study published in Advanced Materials, researchers report the coexistence of topological spin textures of merons, anti-merons, and skyrmions in a single ferromagnet.