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 ...

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

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 ...

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 ...

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 ...

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.