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4D Printing Self-Sensing and Load-Carrying Smart Components

  • Yi Qin
  • , Jianxin Qiao*
  • , Shuai Chi
  • , Huichun Tian
  • , Zexu Zhang
  • , He Liu
  • *Corresponding author for this work
  • School of Mechatronics Engineering, Harbin Institute of Technology
  • Beijing Institute of Astronautical Systems Engineering
  • Research Institute of Petroleum Exploration and Development

Research output: Contribution to journalArticlepeer-review

Abstract

In the past decade, 4D printing has received attention in the aerospace, automotive, robotics, and biomedical fields due to its lightweight structure and high productivity. Combining stimulus-responsive materials with 3D printing technology, which enables controllable changes in shape and mechanical properties, is a new technology for building smart bearing structures. A multilayer smart truss structural component with self-sensing function is designed, and an internal stress calibration strategy is established to better adapt to asymmetric loads. A material system consisting of continuous carbon fibers and polylactic acid was constructed, and an isosceles trapezoidal structure was chosen as the basic configuration of the smart component. The self-inductive properties are described by analyzing the relationship between the pressure applied to the specimen and the change in the specimen’s own resistance. Load-carrying capacity is realized by electrically heating the continuous carbon fibers in the component. Thermal deformation calibrates internal stress and enhances the load-carrying ability of the component over 50%. The experimental results demonstrate that the truss structure designed in this paper has strong self-induction, self-driving ability, and asymmetric load adaptation ability at the same time. This verifies that the 4D-printed smart component can be used as a load-carrying element, which broadens the application scope of smart components.

Original languageEnglish
Article number5903
JournalMaterials
Volume17
Issue number23
DOIs
StatePublished - Dec 2024
Externally publishedYes

Keywords

  • 4D printing
  • fused deposition modeling
  • intelligent component
  • self-sensing

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