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  Teaching solid mechanics to artificial intelligence—a fast solver for heterogeneous materials

Mianroodi, J. R., Hamidi Siboni, N., & Raabe, D. (2021). Teaching solid mechanics to artificial intelligence—a fast solver for heterogeneous materials. npj Computational Materials, 7: 99. doi:10.1038/s41524-021-00571-z.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0009-03E5-1 Version Permalink: https://hdl.handle.net/21.11116/0000-000B-1C10-4
Genre: Journal Article

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s41524-021-00571-z.pdf (Publisher version), 5MB
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2021
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https://creativecommons.org/licenses/by/4.0/

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 Creators:
Mianroodi, Jaber Rezaei1, Author           
Hamidi Siboni, Nima2, Author           
Raabe, Dierk3, Author           
Affiliations:
1Computational Sustainable Metallurgy, Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society, ou_3243050              
2DeepMetis, Lohmühlenstraße 65, 12435 Berlin, Germany, ou_persistent22              
3Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society, ou_1863381              

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Language(s): eng - English
 Dates: 2021-07-012021
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41524-021-00571-z
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Title: npj Computational Materials
  Abbreviation : npj Comput. Mater.
Source Genre: Journal
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Pages: - Volume / Issue: 7 Sequence Number: 99 Start / End Page: - Identifier: ISSN: 2057-3960
CoNE: https://pure.mpg.de/cone/journals/resource/2057-3960