Furthermore, the quest to apply entropy in machine learning algorithms aims to teach machines not only to process data but also to comprehend and predict the inherent unpredictability of the ...

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 ...

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 ...

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 ...

The concept of entropy—commonly understood as “disorder”—was developed in the 19th century by Sadi Carnot and Rudolf Clausius, who were searching for the most efficient way to convert ...