Highly Elastic, Transparent, and Conductive 3D‐Printed Ionic Composite Hydrogels

Abstract

Despite extensive progress to engineer hydrogels for a broad range of technologies, practical applications have remained elusive due to their (until recently) poor mechanical properties and lack of fabrication approaches, which constrain active structures to simple geometries. This study demonstrates a family of ionic composite hydrogels with excellent mechanical properties that can be rapidly 3D‐printed at high resolution using commercial stereolithography technology. The new material design leverages the dynamic and reversible nature of ionic interactions present in the system with the reinforcement ability of nanoparticles. The composite hydrogels combine within a single platform tunable stiffness, toughness, extensibility, and resiliency behavior not reported previously in other engineered hydrogels. In addition to their excellent mechanical performance, the ionic composites exhibit fast gelling under near‐UV exposure, remarkable conductivity, and fast osmotically driven actuation. The design of such ionic composites, which combine a range of tunable properties and can be readily 3D‐printed into complex architectures, provides opportunities for a variety of practical applications such as artificial tissue, soft actuators, compliant conductors, and sensors for soft robotics.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 17, 2017
Source ID
10.1002/adfm.201701807

Entities

People

  • Emmanuel P. Giannelis
  • Jeremy Odent
  • Kevin Kruemplestaedter
  • Robert F Shepherd
  • Thomas J Wallin
  • Wenyang Pan

Organizations

  • Army Research Office
  • Belgian American Educational Foundation
  • Cornell University
  • King Abdullah University of Science and Technology
  • National Science Foundation
  • Qatar National Research Fund

Tags

Fields of Study

  • Materials science

Readers

  • Nanoscale Plasmonic Nanotechnology
  • Reinforced Composite Materials
  • Thin Film Deposition Science.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Autonomy
  • Biotechnology