Light‐Responsive Chemistry to Enable Tunable Interface‐Dependent Mechanical Properties in Composites

Abstract

This work shows the potential of using stimuli‐responsive interfacial adhesion as a means to control interface‐dependent properties in nanocomposites, which could enable interesting applications, such as remote shaping of structural materials, adaptive soft robotics, and tunable intrinsic material damping. In this approach, covalent interfacial bonding is triggered by exposure to an ultraviolet light stimulus, while the degree of interfacial interaction is varied with irradiation duration. To demonstrate the applicability of the technique, polydimethylsiloxane (PDMS) is considered with carbon nanotube (CNT) fillers functionalized with the photoreactive molecule benzophenone. For this specific exemplar material system, the elastic modulus increases by as much as 93%, along with substantial increases in yield stress. The variation with irradiation time is shown to provide the high degree of spatial control needed to engineer heterogeneous materials with desired behavior. While the technique developed in this work is demonstrated on a CNT/PDMS system, the chemistry is generally applicable to a variety of organic filler/matrix combinations, expanding the utility of this interfacial control method to a wide range of material systems. Due to the amenability of this approach to layer‐by‐layer construction, this work shows the potential as an additive manufacturing technique for engineering materials on‐demand with necessary heterogeneous make‐ups.

Document Details

Document Type
Pub Defense Publication
Publication Date
Apr 03, 2018
Source ID
10.1002/admi.201800038

Entities

People

  • Bryan Glaz
  • Frank Gardea
  • Shashi P. Karna
  • Xiyuan Cheng
  • YuHuang Wang
  • Zhiwei Peng
  • Zhongjie Huang

Organizations

  • Air Force Office of Scientific Research
  • Army Research Office
  • United States Army Research Laboratory
  • University of Maryland

Tags

Fields of Study

  • Materials science

Readers

  • Computational Modeling and Simulation
  • Nanocomposite Materials Science
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control