Efficient and transferable machine learning potentials for the simulation of crystal defects in bcc Fe and W-Reference-Cited by-同舟云学术

Efficient and transferable machine learning potentials for the simulation of crystal defects in bcc Fe and W

Published:2021-10-21 Issue:10 Volume:5 Page:
ISSN:2475-9953
Container-title:Physical Review Materials
language:en
Short-container-title:Phys. Rev. Materials

Author:

Goryaeva Alexandra M.^ORCID,Dérès Julien,Lapointe Clovis,Grigorev Petr,Swinburne Thomas D.,Kermode James R.^ORCID,Ventelon Lisa,Baima Jacopo^ORCID,Marinica Mihai-Cosmin

Publisher

American Physical Society (APS)

Subject

Physics and Astronomy (miscellaneous),General Materials Science

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevMaterials.5.103803/fulltext

Reference170 articles.

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3. A simple empirical N-body potential for transition metals

4. Thermodynamical and structural properties of f.c.c. transition metals using a simple tight-binding model

5. Multilayer relaxation at surfaces of body-centered-cubic transition metals

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