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 ...

Penn State researchers created seven new high-entropy oxides by removing oxygen during synthesis, enabling metals that normally destabilize to form rock-salt ceramics. Machine learning helped identify ...

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 ...

In an article recently published in the open-access journal npj Computational Materials, researchers discussed the intelligent framework based on machine learning (ML) for finding refractory ...

Supercomputer simulations are helping scientists discover new high-entropy alloys. XSEDE allocations on TACC's Stampede2 supercomputer supported density function theory calculations for largest ...