Information theory provides a mathematical framework for quantifying information and uncertainty, forming the backbone of modern communication, signal processing, and data analysis. Central to this ...

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 ...

This is a preview. Log in through your library . Abstract Active learning (AL) technique is the classification of remote sensing images, where collecting efficient training data is costly in terms of ...

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 ...

As a measurement of a system's randomness, entropy has specific scientific meaning. Last month, we saw how entropy can be scientifically defined in terms As a measurement of a system's randomness, ...

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 the ...

Entropy is also a measure of the uncertainty or ignorance of an observer observing the system’s macrostate and not knowing the specific microstate. Because states with higher disorder have more ...