Cited by 557Machine Learning in Materials ScienceAdditive Manufacturing and 3D Printing TechnologiesCellular and Composite Structures

Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment

Open access
Gu, Grace X., Chen, Chun-Teh, Richmond, Deon J., Buehler, Markus J.·2018·Materials Horizons

Abstract

A new approach to design hierarchical materials using convolutional neural networks is proposed and validated through additive manufacturing and testing.

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Crossref · 10.1039/c8mh00653a

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  • ML is applied to improve AM processes through failure detection or material design.

    “ML is applied to improve those processes, for example through failure detection [722,730] or material design [309].”

    From Tackling climate change with machine learning (2023) · cites this paper as [309]

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Cites

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Research works printed but not linked: 33

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Cited by

Sorted by citations

Authors
Gu, G. X., Chen, C.-T., Richmond, D. J., & Buehler, M. J.
Affiliations
Massachusetts Institute of Technology (US)
Corresponding author
Buehler, Markus J.
Venue
Materials Horizons
Published
2018
Volume
5
Issue
5
Pages
939-945
ISSN
  • 2051-6347 (ISSN-L)
  • 2051-6355
OpenAlex
W2883482411
Cited by
556
References
35
Citations by year
2026: 53 · 2025: 72 · 2024: 85 · 2023: 85 · 2022: 87 · 2021: 71 · 2020: 71 · 2019: 30 · 2018: 2
FWCI
16.23
Type
journal article
Language
en
Open access
Locations
  • Materials Horizons (publishedVersion, cc-by)
  • The Royal Society of Chemistry
Funders
  • Office of Naval Research (N000141612333)
  • Air Force Office of Scientific Research (FATE MURI FA9550-15-1-0514)
Topics
  • Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
  • Physical Sciences › Engineering › Automotive Engineering › Additive Manufacturing and 3D Printing Technologies
  • Physical Sciences › Engineering › Mechanical Engineering › Cellular and Composite Structures
Keywords
biomimetic design, convolutional neural networks, machine learning for materials design, additive manufacturing, mechanical testing of composites

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