Reprocessable and Mechanically Tailored Soft Architectures Through 3D Printing of Elastomeric Block Copolymers

Alice S. Fergerson, Benjamin H. Gorse, Shawn M. Maguire, Emily C. Ostermann, Emily C. Davidson

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Thermoplastic elastomers (TPEs) are nanostructured, melt-processable, elastomeric block copolymers. When TPEs that form cylindrical or lamellar nanostructures are macroscopically oriented, their material properties can exhibit several orders of magnitude of anisotropy. Here it is demonstrated that the flows applied during the 3D printing of a cylinder-forming TPE enable hierarchical control over material nanostructure and function. It is demonstrated that 3D printing allows for control over the extent of nanostructural and mechanical anisotropy and that thermal annealing of 3D printed structures leads to highly anisotropic properties (up to 85 × anisotropic tensile modulus). This approach is leveraged to print functional soft 3D architectures with tunable local and macroscopic mechanical responses. Further, these printed TPEs intrinsically achieve melt-reprocessability over multiple cycles, reprogrammability, and robust self-healing via a brief period of thermal annealing, enabling facile fabrication of highly tunable, robust, and recyclable soft architectures.

Original languageEnglish (US)
Article number2411812
JournalAdvanced Functional Materials
Volume34
Issue number48
DOIs
StatePublished - Nov 26 2024
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • General Chemistry
  • Biomaterials
  • General Materials Science
  • Condensed Matter Physics
  • Electrochemistry

Keywords

  • 3D printing
  • flow-induced alignment
  • hierarchical structures
  • thermoplastic elastomers

Fingerprint

Dive into the research topics of 'Reprocessable and Mechanically Tailored Soft Architectures Through 3D Printing of Elastomeric Block Copolymers'. Together they form a unique fingerprint.

Cite this