Machine learning assisted design of Fe-Ni-Cr-Al based multi-principal elements alloys with ultra-high microhardness and unexpected wear resistance
In this work, machine learning (ML) technique was used to discovery new multi-principal elements alloys (MPEAs) with desirable properties. Generalized Regression Neural Network (GRNN) showed high accuracy to construct the composition-microhardness model and was used for microhardness prediction and...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-11-01
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| Series: | Journal of Materials Research and Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2238785424025638 |
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