Sub-surface imaging of carbon nanotube-polymer composites using dynamic AFM methods

Maria J. Cadena, University of the Andes Colombia
Rocio Misiego, Birck Nanotechnology Center, Purdue University
Kyle C. Smith, Birck Nanotechnology Center, Purdue University
Alba Avila, University of the Andes Colombia
R. Byron Pipes, Purdue University
Ronald Reifenberger, Birck Nanotechnology Center, Purdue University
Arvind Raman, Birck Nanotechnology Center, Purdue University

Date of this Version

4-5-2013

Citation

Nanotechnology, Volume 24, Number 13

Abstract

High-resolution sub-surface imaging of carbon nanotube (CNT) networks within polymer nanocomposites is demonstrated through electrical characterization techniques based on dynamic atomic force microscopy (AFM). We compare three techniques implemented in the single-pass configuration: DC-biased amplitude modulated AFM (AM-AFM), electrostatic force microscopy (EFM) and Kelvin probe force microscopy (KPFM) in terms of the physics of sub-surface image formation and experimental robustness. The methods were applied to study the dispersion of sub-surface networks of single-walled nanotubes (SWNTs) in a polyimide (PI) matrix. We conclude that among these methods, the KPFM channel, which measures the capacitance gradient (partial derivative C=partial derivative d) at the second harmonic of electrical excitation, is the best channel to obtain high-contrast images of the CNT network embedded in the polymer matrix, without the influence of surface conditions. Additionally, we propose an analysis of the partial derivative C=partial derivative d images as a tool to characterize the dispersion and connectivity of the CNTs. Through the analysis we demonstrate that these AFM-based sub-surface methods probe sufficiently deep within the SWNT composites, to resolve clustered networks that likely play a role in conductivity percolation. This opens up the possibility of dynamic AFM-based characterization of sub-surface dispersion and connectivity in nanostructured composites, two critical parameters for nanocomposite applications in sensors and energy storage devices.

Discipline(s)

Nanoscience and Nanotechnology

 

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