Predicting the stacking fault energy in FCC high-entropy alloys based on data-driven machine learning
The properties of high-entropy alloys (HEAs) depend primarily on the composition and content of elements. However, getting the optimal composition of alloying elements through the traditional ''trial and error'' method is challenging, especially for non-equiatomic HEAs with a wid...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-09-01
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| Series: | Journal of Materials Research and Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2238785423020070 |