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Sensitivity increase of 3D printed, self-sensing, carbon fibers structures with conductive filament matrix

Matei Drilea, Alexander Dijkshoorn, Gusthavo Ribeiro Salomao, Stefano Stramigioli, Gijs Krijnen

3d-printingcompositescarbon-fibersensorsconductive-filament

Abstract

The excellent structural and piezoresistive properties of continuous carbon fiber make it suitable for both structural and sensing applications. This work studies the use of 3D printed, continuous carbon fiber reinforced beams as self-sensing structures. It is demonstrated how the sensitivity of these carbon fiber strain gauges can be increased irreversibly by means of a pretreatment by 'breaking-in' the sensors with a large compressive bending load. The increase in the gauge factor is attributed to local progressive fiber failure, due to the combination of the thermal residual stress from the printing process and external loading. The coextrusion of conductive filament around the carbon fibers is demonstrated as a means of improving the reliability, noise and electrical connection of the sensors.

Summary

This paper demonstrates a novel approach to creating functional composite structures with consumer-accessible 3D printing technology. Key findings:

  • Dual-Material Printing: Combines continuous carbon fiber with conductive filament through coextrusion
  • Self-Sensing Capability: Carbon fiber’s piezoresistive properties enable the printed structure to act as its own strain gauge
  • Sensitivity Enhancement: A “breaking-in” process (applying large compressive bending loads) irreversibly increases the gauge factor
  • Mechanism: Thermal residual stresses from printing combine with external loading to cause local fiber micro-failures, which enhance sensitivity
  • Practical Benefits: Coextruding conductive filament around carbon fibers improves:
    • Electrical connection reliability
    • Reduced noise in measurements
    • Better overall sensor performance

This is particularly relevant for makers interested in creating smart structures - parts that can sense their own deformation, which could be useful for robotics, prosthetics, or structural health monitoring applications.

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