Uncovering the effects of interface-induced ordering of liquid on crystal growth using machine learning
Crystallization is a challenging process to model quantitatively. Here the authors use machine learning and atomistic simulations together to uncover the role of the liquid structure on the process of crystallization and derive a predictive kinetic model of crystal growth.
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| Auteurs principaux: | , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2020
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/964c406f580d4fc48ff08ec6be350803 |
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