2024
DOI: 10.3390/cryst14050429
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Machine Learning-Based Prediction of Stability in High-Entropy Nitride Ceramics

Tianyu Lin,
Ruolan Wang,
Dazhi Liu

Abstract: The field of materials science has experienced a transformative shift with the emergence of high-entropy materials (HEMs), which possess a unique combination of properties that traditional single-phase materials lack. Among these, high-entropy nitrides (HENs) stand out for their exceptional mechanical strength, thermal stability, and resistance to extreme environments, making them highly sought after for applications in aerospace, defense, and energy sectors. Central to the design of these materials is their e… Show more

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