Using the second-nearest neighboring atoms to predict metallic glass stability can help researchers more accurately model the disordered solid with strong, elastic properties, according to a recent ...

Imagine having a super-powered lens that uncovers hidden secrets of ultra-thin materials used in our gadgets. Research led by University of Florida engineering professor Megan Butala enables a novel ...

A long-standing mystery in materials science is beginning to unravel as researchers directly probe the hidden atomic complexity of relaxor ferroelectrics.

Machine learning and specifically, deep learning, is a powerful tool to establish the presence (or absence) of microstructure correlations to bulk properties with its ability to flesh out ...

Empa researchers led by Simon Gramatte (front) and Vladyslav Turlo have succeeded for the first time in simulating amorphous aluminum oxide with hydrogen inclusions with atomic precision. Aluminum ...