AI-Enabled Materials Design of Non-Periodic 3D Architectures With Predictable Direction-Dependent Elastic Properties

Wen Jing Deng, Siddhant Kumar, Alberto Vallone, Dennis M. Kochmann, Julia R. Greer*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
64 Downloads (Pure)

Abstract

Natural porous materials have exceptional properties—for example, light weight, mechanical resilience, and multi-functionality. Efforts to imitate their properties in engineered structures have limited success. This, in part, is caused by the complexity of multi-phase materials composites and by the lack of quantified understanding of each component's role in overall hierarchy. This challenge is twofold: 1) computational. because non-periodicity and defects render constructing design guidelines between geometries and mechanical properties complex and expensive and 2) experimental. because the fabrication and characterization of complex, often hierarchical and non-periodic 3D architectures is non-trivial.

Original languageEnglish
Article number2308149
Number of pages9
JournalAdvanced Materials
Volume36
Issue number34
DOIs
Publication statusPublished - 2024

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • additive manufacturing
  • anisotropy
  • biomimetic
  • machine learning
  • scaffold design

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