Bio-inspired 3D printing of self-growing multinetwork elastomer composites

Dong Wu, Zeang Zhao*, Hongshuai Lei, Hao Sen Chen, Qiang Zhang, Panding Wang, Daining Fang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Natural tissues possess the self-strengthening ability through biological growth, during which additional building blocks are transported into the tissues and attached to the pre-existing microstructures. In contrast, synthetic materials are typically static, meaning neither their dimensions nor their mechanical properties are able to be altered after the materials are manufactured into specific structures. Recently the concept of bio-inspired synthetic material arises, aiming at developing materials with dynamically programmable performances. Based on the idea of multinetwork (MN) elastomer, we propose a solvent-free elastomer composite system that can be strengthened through tunable self-growth cycles. Resembling biological tissues, chemical structures of the composite remain constant after self-growing, while its dimension, modulus, strength and swelling ability can be programmed on demand. The elastomer composite is naturally compatible with Digital Light Processing (DLP) 3D printing, which directly enables the fast manufacturing of high-precision structures. Applications of the self-growing composites in metamaterials with tunable mechanical performance and waterproof structures are exhibited at the same time.

Original languageEnglish
Article number114777
JournalComposite Structures
Volume279
DOIs
Publication statusPublished - 1 Jan 2022

Keywords

  • 3D print
  • Elastomer composites
  • Multinetwork
  • Self-growing

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