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 ...

Since their discovery at Drexel University in 2011, MXenes — a family of nanomaterials with unique properties of durability, ...

Keeping reduction of computation time as the objective, here we present, an entropy query by bagging (EQB)-based AL approach in the extreme learning machine (ELM) framework for remote sensing image ...

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 ...

Entropy is a confusing concept, but it is also extremely useful for quantifying the properties of complex systems like the human brain. This article attempts to demystify the term.

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 ...