Dynamics of dual-junction-functionality associative polymer networks with ion and nanoparticle metal-coordinate cross-link junctions

Abstract

We provide a canonical introduction to dual-junction-functionality associative polymer networks, which combine high and low functionality (f) dynamic cross-link junctions to impart load-bearing, dissipation, and self-repairing ability to the network. This unique type of network configuration offers an alternative to traditional dual-junction networks consisting of covalent and reversible cross-links. The high-f junctions can provide load-bearing abilities similar to a covalent cross-link while retaining the ability to self-repair and concurrently confer stimuli-responsive properties arising from the high-f junction species. We demonstrate the mechanical properties of this design motif using metal-coordinating polymer hydrogel networks, which are dynamically cross-linked by different ratios of metal nanoparticle (high-f) and metal ion (low-f) cross-link junctions. We also demonstrate the spontaneous self-assembly of nanoparticle-cross-linked polymers into anisotropic sheets, which may be generalizable for designing dual-junction-functionality associative networks with low volume fraction percolated high-f networks.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 01, 2022
Source ID
10.1122/8.0000410

Entities

People

  • Bavand Keshavarz
  • Brian S. Chapman
  • Gareth McKinley
  • Jake Song
  • Joseph B Tracy
  • Niels Holten-Andersen
  • Pangkuan Chen
  • Qiaochu Li

Organizations

  • Army Research Office
  • Massachusetts Institute of Technology
  • National Science Foundation
  • North Carolina State University

Tags

Readers

  • Nanocomposite Materials Science
  • Neural Network Machine Learning.

Technology Areas

  • Biotechnology