Self-Assembled Robust 2D Networks from Magneto-Elastic Bars

Xinyan Yang, Junqing Leng, Cheng Sun, Sinan Keten*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Magneto-elastic materials facilitate features such as shape programmability, adaptive stiffness, and tunable strength, which are critical for advances in structural and robotic materials. Magneto-elastic networks are commonly fabricated by employing hard magnets embedded in soft matrices to constitute a monolithic body. These architected network materials have excellent mechanical properties but damage incurred in extreme loading scenarios are permanent. To overcome this limitation, we present a novel design for elastic bars with permanent fixed dipole magnets at their ends and demonstrate their ability to self-assemble into magneto-elastic networks under random vibrations. The magneto-elastic unit configuration, most notably the orientation of end dipoles, is shown to dictate the self-assembled network topology, which can range from quasi-ordered triangular lattices to stacks or strings of particles. Network mechanics are probed with uniaxial tensile tests and design criteria for forming stable lightweight 2D networks are established. It is shown that these magneto-elastic networks rearrange and break gracefully at their magnetic nodes under large excitations and yet recover their original structure at moderate random excitations. This work paves the way for structural materials that can be self-assembled and repaired on-the-fly with random vibrations, and broadens the applications of magneto-elastic soft materials.

Original languageEnglish (US)
Article number2202189
JournalAdvanced Materials Technologies
Issue number14
StatePublished - Jul 24 2023


  • magneto-elastic networks
  • particle dynamics simulations
  • self-assembly
  • self-healing

ASJC Scopus subject areas

  • General Materials Science
  • Mechanics of Materials
  • Industrial and Manufacturing Engineering


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