Explore the groundbreaking 7th Blind Test of Crystal Structure Prediction methods, where scientists are learning to predict nature's blueprints with startling accuracy.
Discover how electric fields are enabling precise control of material microstructures through grain boundary engineering, creating continuously graded materials with optimized properties.
Explore how machine learning and multi-fidelity modeling are transforming materials science by bridging atomic and macroscopic scales.
Exploring how multiscale modeling challenges traditional atomistic simulation approaches in materials science and biological systems.
How scientists are using petascale computing and multiscale modeling to predict material failures in microsystems and ensure technological reliability.
Explore the fascinating progress in fiber structure analysis techniques, from X-ray crystallography to computational models revolutionizing materials science.
Explore the evolution of polymer processing into macromolecular engineering, from controlled polymerization to AI-driven discovery and sustainable solutions.
Discover how unsupervised machine learning is revolutionizing atomic-scale materials science by decoding chemical transformation pathways from atomically-resolved imaging data.