Unraveling phase prediction in high entropy alloys: A synergy of machine learning, deep learning, and ThermoCalc, validation by experimental analysis
The phase formation in high entropy alloys (HEAs) presents a significant challenge due to the complexity of their composition and the intricate interactions between multiple elements. The machine learning (ML) and deep learning (ANN) models play a crucial role in phase prediction for HEAs owing to t...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-03-01
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| Series: | Journal of Materials Research and Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2238785424001455 |