Setting the standard for machine learning in phase field prediction: a benchmark dataset and baseline metrics
Abstract Phase field models are an important mesoscale method that serves as a bridge between the atomic scale and the macroscale, used for modeling complex phenomena at the microstructure level. Machine learning can be employed to accelerate these simulations, enabling faster and more efficient ana...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-11-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-024-04128-9 |
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