3D Printable Modular Soft Elastomers from Physically Cross-linked Homogeneous Associative Polymers

由物理交联的均相缔合聚合物制成的可3D打印模块化软弹性体

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Abstract

Three-dimensional (3D) printing of elastomers enables the fabrication of many technologically important structures and devices. However, there remains a critical need for the development of reprocessable, solvent-free, soft elastomers that can be printed without the need for post-treatment. Herein, we report modular soft elastomers suitable for direct ink writing (DIW) printing by physically cross-linking associative polymers with a high fraction of reversible bonds. We designed and synthesized linear-associative-linear (LAL) triblock copolymers; the middle block is an associative polymer carrying amide groups that form double hydrogen bonding, and the end blocks aggregate to hard glassy domains that effectively act as physical cross-links. The amide groups do not aggregate to nanoscale clusters and only slow down polymer dynamics without changing the shape of the linear viscoelastic spectra; this enables molecular control over energy dissipation by varying the fraction of the associative groups. Increasing the volume fraction of the end linear blocks increases the network stiffness by more than 100 times without significantly compromising the extensibility. We created elastomers with Young's moduli ranging from 8 kPa to 8 MPa while maintaining the tensile breaking strain around 150%. Using a high-temperature DIW printing platform, we transformed our elastomers to complex, highly deformable 3D structures without involving any solvent or post-print processing. Our elastomers represent the softest melt reprocessable materials for DIW printing. The developed LAL polymers synergize emerging homogeneous associative polymers with a high fraction of reversible bonds and classical block copolymer self-assembly to form a dual-cross-linked network, providing a versatile platform for the modular design and development of soft melt reprocessable elastomeric materials for practical applications.

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