Related Experiment Video
Updated: May 27, 2026

09:38
Strain Sensing Based on Multiscale Composite Materials Reinforced with Graphene Nanoplatelets
Published on: November 7, 2016
Low-loss, high-permittivity composites made from graphene nanoribbons
Ayrat Dimiev1, Wei Lu, Kyle Zeller
1Department of Chemistry, Rice University, MS-222, 6100 Main Street, Houston, Texas 77005, USA.
ACS Applied Materials & Interfaces
|November 8, 2011
Summary
Researchers developed a new composite material using graphene nanoribbons in a dielectric matrix. This material offers tunable low loss and high permittivity, demonstrating how nanoscale filler structure impacts bulk properties.
Area of Science:
- Materials Science
- Nanotechnology
- Electrical Engineering
Background:
- Dielectric composite materials are crucial for electronic applications.
- Controlling electrical loss and permittivity is essential for device performance.
- Graphene nanoribbons offer unique electrical and structural properties.
Purpose of the Study:
- To create a novel composite material with tunable dielectric properties.
- To investigate the relationship between graphene nanoribbon content and material characteristics.
- To demonstrate the impact of nanoscale filler structure on macroscopic properties.
Main Methods:
- Incorporation of graphene nanoribbons into a dielectric host matrix.
- Systematic variation of graphene nanoribbon content.
- Characterization of dielectric properties (permittivity and loss).
Main Results:
- The composite exhibited remarkably low dielectric loss at high permittivity values.
- Tunable loss and permittivity were achieved by adjusting graphene nanoribbon concentration.
- A wide range of desirable dielectric properties could be obtained.
Conclusions:
- The developed composite material shows significant potential for electronic applications requiring specific dielectric properties.
- The study highlights the effectiveness of graphene nanoribbons as fillers for tuning composite behavior.
- Nanoscale structural modifications of fillers can predictably alter macroscopic material performance.

