Oct 19, 2012
Automated routine reveals dispersion and orientation of carbon nanotubes in polymer composites
Carbon nanotube(CNT)/polymer composites offer a range of useful properties such as high strength, electrical and thermal conductivity, and a low coefficient of thermal expansion, but these properties are strongly dependent on the spatial distribution and orientation of CNTs in the polymer matrix. Capturing this information would help developers to predict the properties of CNT/polymer composites more accurately, but it can be a difficult task. CNTs may be present in large numbers and typically appear as dots or as tubes of different lengths depending on their orientation relative to the observation plane.
Now, researchers from Georgia Institute of Technology and Harvard Medical School in the US have incorporated a shape identification function that is often used in biomedical image analysis to identify individual CNTs in images of CNT composites automatically.
First, CNTs with different dimensions and shapes are automatically extracted from SEM images of the sample. Then the spatial and orientational dispersion of the extracted CNTs are computed, respectively, as a spatial dispersion index and an orientational dispersion index.
The obtained indices will be a great help in optimizing processing conditions and in predicting the properties of the composite. Also, this method can be extended to other polymer composites with high-aspect-ratio fillers.
Full details can be found in the journal Nanotechnology.
About the author
Yi Gao is a member of the Psychiatry Neuroimaging Laboratory at Harvard Medical School, Boston.