The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment
Open accessAbstract
A new approach to design hierarchical materials using convolutional neural networks is proposed and validated through additive manufacturing and testing.
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“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
Data Mining: Practical Machine Learning Tools and Techniques
Witten, I. H., Frank, E., & Hall, M. A. (2011) · Elsevier eBooks · doi:10.1016/c2009-0-19715-5 · Cited by 25,543
Bioinspired structural materials
Wegst, U. G. K., Bai, H., Saiz, E., Tomsia, A. P., & Ritchie, R. O. (2014) · Nature Materials · doi:10.1038/nmat4089 · Cited by 4,735
The conflicts between strength and toughness
Ritchie, R. O. (2011) · Nature Materials · doi:10.1038/nmat3115 · Cited by 3,989
Selection of relevant features and examples in machine learning
Blum, A. L., & Pat Langley, B. (1997) · Artificial Intelligence · doi:10.1016/s0004-3702(97)00063-5 · Cited by 3,294
Nature’s hierarchical materials
Fratzl, P., & Weinkamer, R. (2007) · Progress in Materials Science · doi:10.1016/j.pmatsci.2007.06.001 · Cited by 2,788
The status, challenges, and future of additive manufacturing in engineering
Gao, W., Zhang, Y., Ramanujan, D., Ramani, K., Chen, Y., Williams, C. B., Wang, C. C. L., Shin, Y. C., Zhang, S., & Zavattieri, P. D. (2015) · Computer-Aided Design · doi:10.1016/j.cad.2015.04.001 · Cited by 2,657
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Face recognition by independent component analysis
Bartlett, M. S., Movellan, J. R., & B, T. J. S. A. (2002) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2002.804287 · Cited by 1,951
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3D‐Printing of Lightweight Cellular Composites
Compton, B. G., & Lewis, J. A. (2014) · Advanced Materials · doi:10.1002/adma.201401804 · Cited by 1,677
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Research works printed but not linked: 2
- D. Brackett , I.Ashcroft and R.Hague , Proceedings of the solid freeform fabrication symposium , 2011 , pp. 348–362
- Liu, 2015, Sci. Rep., 5, 1551
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Voxelated soft matter via multimaterial multinozzle 3D printing
Skylar‐Scott, M. A., Mueller, J., Visser, C. W., & Lewis, J. A. (2019) · Nature · doi:10.1038/s41586-019-1736-8 · Cited by 1,031
Magnetic Soft Materials and Robots
Kim, Y., & Zhao, X. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00481 · Cited by 920
Benedetti, M., du Plessis, A., Ritchie, R. O., Dallago, M., Razavi, N., & Berto, F. (2021) · Materials Science and Engineering: R: Reports · doi:10.1016/j.mser.2021.100606 · Cited by 788
Machine learning in additive manufacturing: State-of-the-art and perspectives
Wang, C., Tan, X., Tor, S. B., & Lim, C. S. (2020) · Additive manufacturing · doi:10.1016/j.addma.2020.101538 · Cited by 736
Artificial intelligence and machine learning in design of mechanical materials
Guo, K., Yang, Z., Yu, C., & Buehler, M. J. (2020) · Materials Horizons · doi:10.1039/d0mh01451f · Cited by 732
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Metadata
- 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
- Publisher
- Royal Society of Chemistry (RSC)
- 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
- hybrid
- doi.org
- 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 › Industrial and Manufacturing 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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