Materials informatics for the screening of multi-principal elements and high-entropy alloys
The identification of high entropy alloys is challenging given the vastness of the compositional space associated with these systems. Here the authors propose a supervised learning strategy for the efficient screening of high entropy alloys, whose hardness predictions are validated by experiments.
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| Main Authors: | , , , , , , |
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| Format: | article |
| Language: | EN |
| Published: |
Nature Portfolio
2019
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| Subjects: | |
| Online Access: | https://doaj.org/article/fc87f74cda1d42ca8e000180ad4c8e7c |
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