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Stretchable and self-healable materials with excellent mechanical performance hold great promise for applications in flexible functional devices. Despite rapid developments, achieving high mechanical strength, extreme stretchability, and rapid self-healing capability in self-healing materials remains challenging. Here, inspired by the hierarchical structure and unique network of connective tissue, we fabricated a class of bionic nanocomposites with high stretchability, outstanding mechanical strength, and rapid self-healing ability by integrating the bottlebrush copolymer functionalized graphene oxide (BCP@GO) into a polyurethane (PU) matrix via in-situ polymerization. The bottlebrush copolymer (BCP) acted as a bond bridge for linking the GO nanosheets (noncovalent interaction) and PU chains (covalent and hydrogen-bond interaction). The covalent interactions were responsible for providing high mechanical strength, and the abundant hydrogen-bond-based cross-links realized extreme stretchability and rapid self-healing capability. The resultant BCP@GO/PU nanocomposite with only 0.5 wt.% GO loading exhibited excellent mechanical properties (tensile strength increased by 52.1%, up to 28.6 MPa; toughness increased by 70.8%, up to 256.9 MJ/m3; elongation at break increased by 12.8%, up to 1847.2%), exceptional rapid and efficient self-healing ability (~ 99% with 20 s NIR irradiation), as well as superior shape memory and recyclable capability. This study develops a new strategy for designing high-performance self-healing nanocomposites and unfolds broad application prospects in smart materials.


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High-strength, stretchable, and NIR-induced rapid self-healing polyurethane nanocomposites with bio-inspired hybrid cross-linked network

Show Author's information Tianbo DengJunyuan ZhuHe ZhaoBinbin Xu( )Ling Zhang( )Chunzhong Li( )
Key Laboratory for Ultrafine Materials of Ministry of Education, Shanghai Engineering Research Center of Hierarchical Nanomaterials, Frontiers Science Center for Materiobiology and Dynamic Chemistry, School of Materials Science and Engineering, East China University of Science & Technology, Shanghai 200237, China

Abstract

Stretchable and self-healable materials with excellent mechanical performance hold great promise for applications in flexible functional devices. Despite rapid developments, achieving high mechanical strength, extreme stretchability, and rapid self-healing capability in self-healing materials remains challenging. Here, inspired by the hierarchical structure and unique network of connective tissue, we fabricated a class of bionic nanocomposites with high stretchability, outstanding mechanical strength, and rapid self-healing ability by integrating the bottlebrush copolymer functionalized graphene oxide (BCP@GO) into a polyurethane (PU) matrix via in-situ polymerization. The bottlebrush copolymer (BCP) acted as a bond bridge for linking the GO nanosheets (noncovalent interaction) and PU chains (covalent and hydrogen-bond interaction). The covalent interactions were responsible for providing high mechanical strength, and the abundant hydrogen-bond-based cross-links realized extreme stretchability and rapid self-healing capability. The resultant BCP@GO/PU nanocomposite with only 0.5 wt.% GO loading exhibited excellent mechanical properties (tensile strength increased by 52.1%, up to 28.6 MPa; toughness increased by 70.8%, up to 256.9 MJ/m3; elongation at break increased by 12.8%, up to 1847.2%), exceptional rapid and efficient self-healing ability (~ 99% with 20 s NIR irradiation), as well as superior shape memory and recyclable capability. This study develops a new strategy for designing high-performance self-healing nanocomposites and unfolds broad application prospects in smart materials.

Keywords: self-healing materials, recyclability, shape memory, smart nanocomposite, high mechanical property

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Publication history
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Acknowledgements

Publication history

Received: 30 December 2023
Revised: 30 January 2024
Accepted: 08 February 2024
Published: 01 April 2024

Copyright

© Tsinghua University Press 2024

Acknowledgements

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos. 22278140, U22B20143, and 52273008), the Science and Technology Commission of Shanghai Municipality (Nos. 22DZ1205900 and 22ZR1479300), Shanghai Rising-Star Program (No. 23QA1402500), Project supported by Shanghai Municipal Science and Technology Major Project, and the Fundamental Research Funds for the Central Universities.

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