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2/18/2015 | 1 MINUTE READ

SEM-based NDI checks CNT dispersion in composites

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Refined techniques enable quantitative 3D imaging of CNT dispersion within the polymer and better understanding of its impact on CNT composite conductivity.

As reported by Nanowerk.com, lightweight composite materials consisting of polymer matrices with embedded carbon nanotubes (CNTs) offer a unique combination of stiffness and strength with very high thermal and electrical conductivities. Understanding the dispersion of carbon nanotubes within the polymer matrix is critical for constructing the structure-property relationships that can improve the performance of CNT nanocomposites. High-resolution subsurface imaging methods are well suited for this task.

While Scanning Electron Microscopy (SEM) is normally used for surface imaging, it has been used for subsurface imaging but with many issues concerning proper methodology. These issues have been addressed through recent research by Dr. Minhua Zhao, visiting researcher in the Center for Nanoscale Science and Technology at The National Institute of Standards and Technology (NIST, Washington, DC, US) with joint appointment in the department of Materials Science and Engineering at University of Maryland (College Park, MD, US).

"Through extensive experiments – i.e., surface and cross sectional SEM imaging, beam-induced current measurement, focus ion beam milling, 3D reconstruction from stereo SEM images – and Monte Carlo simulations, our findings clarify these issues and help establish SEM subsurface imaging as a useful and facile method to provide quantitative 3D information on CNT dispersions in polymer composites," says Zhao.

Zhao and his collaborators report their non-destructive and high throughput 3D imaging of CNTs embedded in polymer matrix via SEM in a new paper titled, "New insights into subsurface imaging of carbon nanotubes in polymer composites via scanning electron microscopy", featured in the February 2015 issue of Nanotechnology. The technique described can be used to better understand the relationship between dispersion of CNTs in a polymer matrix and conductivity of CNT polymer composites. Compared to the team's previous work, the current technique has a much higher throughput and more quantitative depth information.

The application of these techniques are generally applicable to subsurface imaging of any conducting nanostructures embedded in a dielectric matrix, including graphene polymer composites.

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