Stacking fault energy prediction for austenitic steels: thermodynamic modeling vs. machine learning
Stacking fault energy (SFE) is of the most critical microstructure attribute for controlling the deformation mechanism and optimizing mechanical properties of austenitic steels, while there are no accurate and straightforward computational tools for modeling it. In this work, we applied both thermod...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2020-01-01
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| Series: | Science and Technology of Advanced Materials |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/14686996.2020.1808433 |