Data-driven and topological design of structural metamaterials for fracture resistance

Daicong Da, Yu Chin Chan, Liwei Wang, Wei Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Data science as a promising paradigm provides novel and diverse opportunities for structural metamaterials attaining exceptional mechanical properties. It is demonstrated here that porous structures composed of brittle constitutive materials can be strong and tough through topological optimization and data-driven techniques. We show that brittle fracture properties can be tailored through the linear control of the homogenized stress and non-periodic microstructures from a multiscale perspective. These tough advanced structural metamaterials pave the way to multiscale components with exceptional fracture resistance.

Original languageEnglish (US)
Article number101528
JournalExtreme Mechanics Letters
StatePublished - Jan 2022


  • Brittle fracture
  • Data-driven methods
  • Stress
  • Structural metamaterials
  • Topological design

ASJC Scopus subject areas

  • Bioengineering
  • Chemical Engineering (miscellaneous)
  • Engineering (miscellaneous)
  • Mechanics of Materials
  • Mechanical Engineering


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