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  Computational study of crystal defect formation in Mo by a machine learning molecular dynamics potential

Dominguez Gutierrez, F. J., Byggmästar, J., Nordlund, K., Djurabekova, F., & Toussaint, U. v. (2021). Computational study of crystal defect formation in Mo by a machine learning molecular dynamics potential. Modelling and Simulation in Materials Science and Engineering, 29(5): 055001. doi:10.1088/1361-651X/abf152.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0008-A6F5-8 Version Permalink: https://hdl.handle.net/21.11116/0000-0008-A6F6-7
Genre: Journal Article

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dominguez-gutierrez_computational.pdf (Supplementary material), 2MB
 
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https://doi.org/10.1088/1361-651X/abf152 (Publisher version)
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 Creators:
Dominguez Gutierrez, F. J.1, 2, Author           
Byggmästar, J2, Author
Nordlund, K2, Author
Djurabekova, F2, Author
Toussaint, U. von1, Author           
Affiliations:
1Numerical Methods in Plasma Physics (NMPP), Max Planck Institute for Plasma Physics, Max Planck Society, ou_1856344              
2External Organizations, ou_persistent22              

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Language(s): eng - English
 Dates: 2021
 Publication Status: Published online
 Pages: 15 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1088/1361-651X/abf152
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Title: Modelling and Simulation in Materials Science and Engineering
  Abbreviation : Modelling Simul. Mater. Sci. Eng.
Source Genre: Journal
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Publ. Info: London : IOP Pub.
Pages: - Volume / Issue: 29 (5) Sequence Number: 055001 Start / End Page: - Identifier: ISSN: 0965-0393
CoNE: https://pure.mpg.de/cone/journals/resource/954925581155