Predicting structure zone diagrams for thin film synthesis by generative machine learning
Controlling the microstructure of thin films is vital for tuning their properties. Here, machine learning is applied to obtain synthesis-composition-microstructure relationships in the form of structure zone diagrams for thin films, enabling microstructure prediction.
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| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2020
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/b761d7313f9244cb9fc3e14a15558671 |
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| Sumario: | Controlling the microstructure of thin films is vital for tuning their properties. Here, machine learning is applied to obtain synthesis-composition-microstructure relationships in the form of structure zone diagrams for thin films, enabling microstructure prediction. |
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