Smart material based multilayered microbeam structures for spatial self-deployment and reconfiguration: A residual stress approach

Zhongjing Ren, Chengyang Li, Kecai Xie, Sundeep Mangla, Chang Yong Nam, Fernando Camino, Haipeng Wang, Jianping Yuan, Peng Yan

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Alleviation of the potentially damaging effects induced by residual stresses was comprehensively investigated in previous research. This paper, however, presents a spatially self-deployable and reconfigurable multilayered microbeam which takes advantage of residual stresses and shape memory effects. Reconfigurable mechanism of a typical four-layered microbeam composed of Pt\Ni50Ti50\Ni50Ti50\Pt is introduced, followed by analytical modeling of the maximum distance of the self-deployed gap as functions of variable structural and material parameters, including compressive residual stress in Pt layers and tensile residual stress in Ni50Ti50 layers. Analytical solutions given by the static model agree well with the results obtained via finite element models (FEMs). Fabrication, characterization, and in-situ experiments were carried out to validate the feasibility of deployment of the as-released four-layered microbeam. The maximum distance of the gap was measured to be 41.39 μm at 20 ℃, which could be increased to 51.73 μm thanks to controllable reconfiguration driven by shape memory effects. Theoretical analysis of such self-deployment and reconfiguration suggested a tensile residual stress increase by 52 MPa in Ni50Ti50 layers. The multilayered microbeam structure with capabilities of self-deployment and reconfiguration offers great potential for various emerging applications, such as micro robotics, medical drug delivery devices, and intelligent chip scale spacecraft.

Original languageEnglish
Article number116468
JournalComposite Structures
Volume304
DOIs
StatePublished - 15 Jan 2023

Keywords

  • Multilayered microbeam
  • Reconfiguration
  • Residual stresses
  • Self-deployment
  • Shape memory effect

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