High-entropy alloys (HEAs) represent a transformative class of structural materials defined by near-equimolar proportions of five or more elements. The vast compositional space and complex phase ...

Using a new physics-informed machine learning approach, researchers discovered two new high-entropy alloys with extremely low thermal expansion, a new study reports. The approach could represent a ...

One of the central challenges in modern machine learning is understanding how neural networks generalize knowledge learned from training data to unseen test data. While numerous empirical techniques ...

Dielectric ceramic capacitors are essential core components for electronics, smart grids and new energy vehicles, prized for their high power density. As electronic devices move toward miniaturization ...

Understanding defect dynamics and evolution in high entropy alloys (HEAs) s is complicated due to the wide and intricate configurational space in HEAs. Machine learning techniques have significant ...