Machine learning predictions of surface migration barriers in nucleation and non-equilibrium growth

Experiments and simulations can reveal energetic barriers during atomic-scale growth but are time-consuming. Here, machine learning is applied to single images from kinetic Monte Carlo simulations of sub-monolayer film growth, allowing diffusion barriers and binding energies to be accurately determi...

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Autores principales: Thomas Martynec, Christos Karapanagiotis, Sabine H. L. Klapp, Stefan Kowarik
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/7d4d7877ccbf48aa9043f85191147eca
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