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 ...

High-entropy materials (HEMs) have attracted considerable research attention in battery applications due to exceptional properties such as remarkable structural stability, enhanced ionic conductivity, ...

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 ...

Various modifications have been suggested in the past to extend Shannon entropy to continuous random variables. This article investigates these modifications, and suggests a new entropy measure with ...

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 ...

Department of Computer Science assistant professor Chris Heckman and CIRES research hydrologist Toby Minear have been awarded a Grand Challenge Research & Innovation Seed Grant to create an instrument ...

Georgia Tech researchers introduced a groundbreaking machine learning technique to improve the assessment and analysis of declining oxygen levels in the ocean. Using data from Argo floats (pictured) ...