High-entropy alloys are promising advanced materials for demanding applications, but discovering useful compositions is difficult and expensive due to the vast number of possible element combinations.

By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

Georgia Tech’s Qi Tang is building machine learning (ML) models to accelerate nuclear fusion research, making it more affordable and more accurate. Backed by a grant from the U.S. Department of Energy ...

In order to build the computers and devices of tomorrow, we have to understand how they use energy today. That's harder than it sounds. Memory storage, information processing, and energy use in these ...

Opioid overdoses continue to take a devastating toll across the United States. According to the U.S. Centers for Disease ...

Introduction: As the core equipment in industrial production, rotating machinery bearings play a critical role. However, traditional feature extraction algorithms for vibration signals are susceptible ...

Multielement high-entropy carbides (HECs) provide many opportunities for HECs to obtain optimal combinations of various properties, e.g., high strength and high flexibility, leading to high toughness.