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 ...

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 ...

The review, entitled “Design strategies for high entropy materials in water electrolysis: enhancing activity, stability, and ...

Study: Machine-learning-based intelligent framework for discovering refractory high-entropy alloys with improved high-temperature yield strength. Image Credit: Quardia/Shutterstock.com Background ...

Researchers at Cleveland State University have recently achieved a significant breakthrough in the field of quantum sensing by utilizing machine learning techniques to optimize circuits, successfully ...

The core of this patent lies in constructing a machine learning database, using design parameters of seismic isolation bearings as input data, and bridge target response data as output data.

Entropy is one of the most useful concepts in science but also one of the most confusing. This article serves as a brief introduction to the various types of entropy that can be used to quantify ...