Classification of Carbon Nanotubes using SEM

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A fully PC controlled FE SEM intended for both – for high vacuum as well as for low vacuum operations. Outstanding optical properties, flicker-free...


Research of Carbon-based nanomaterials has revealed a new promising form of carbon - carbon nanotubes (CNTs) - with huge potential in the developing field of nanotechnology. Unique properties and novel applications of CNTs make them potentially useful in wide range of technological applications. Characterization of basic properties of nanotubes is indispensable to the further scientific and industrial development. Scanning electron microscopy (SEM) is one of the most powerful tools in nanotechnology and plays an important role in the research of nanowires and CNTs. The MIRA3 SEM equipped with In-Beam SE and STEM detectors was used to study basic parameters of carbon nanotubes, in order to explore their properties.

Carbon nanotubes were discovered by Sumio Iijima in 1991. CNTs are formed by self-assembling of carbon atoms. They have hollow cylinder structures with diameters of less than 100 nm. 

CNTs exhibit extraordinary strength and unique electrical properties, and they are efficient thermal conductors. These incredible properties give CNTs great potential in a wide range of fields, such as nanotechnology, electronics, optics, materials science and architecture. They might be also used in the construction of body armor.

MIRA3 micrograph of carbon nanotubes obtained with In-Beam SE detector. Evaluation of CNT thickness

Image processing software produced by TESCAN has many unique features which enable an operator to perform advanced image processing, measurement and a range of additional modules for various purposes. A standard part of TESCAN software is a Measurement module which has at its disposal  a set of tools that can be used for measuring any shape within an image with possibility to document the results and add important annotations into the image. 

The module is used for interactive measuring of object parameters in stored as well as in live images with possibility of statistical evaluation .....

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