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Image Analysis Optimization for Quantifying Nanoparticle Dispersions in Polymer-based Nanocomposites Using Transmission Electron Microscopy (TEM)

Published online by Cambridge University Press:  04 February 2011

Anand S. Badami
Affiliation:
The Dow Chemical Company, 1897 Building, Midland, MI 48667
Mark W. Beach
Affiliation:
The Dow Chemical Company, 1897 Building, Midland, MI 48667
Stewart P. Wood
Affiliation:
The Dow Chemical Company, 1897 Building, Midland, MI 48667
Steven J. Rozeveld
Affiliation:
The Dow Chemical Company, 1897 Building, Midland, MI 48667
William A. Heeschen
Affiliation:
The Dow Chemical Company, 1897 Building, Midland, MI 48667
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Abstract

When comparing large numbers of TEM micrographs of insoluble additives in polymer-based nanocomposite systems, the ability to determine or estimate the dispersion quality (i.e. uniformity of size and/or spatial distribution) is often difficult. The objective of this study was to develop a method to quantify dispersions observed in TEM micrographs that enables both a numerical “ranking” to be assigned to individual dispersions as well as tabulation a multitude of images acquired over time. Several methods were reviewed and applied to a set of TEM dispersion images of an insoluble additive in polystyrene. Projected area diameter, particle area, and Euclidean distance between particle centroids were chosen from all the particle size distribution and spatial distribution parameters present in the literature, but none successfully yielded a quantitative indicator of dispersion quality for the micrographs. In contrast, generating cumulative volume percent curves for each sample appeared to be a preferred method of quantifying and comparing dispersions in TEM micrographs. The volume diameter values obtained by this method can be used for “ranking” and tabulation of dispersion quality and account for both “good” additive dispersions (i.e. those with small domains of a narrow size range around 1 μm or less) and “bad” additive dispersions (i.e. those with non-uniform domains ranging in size by several microns or more). As a result, the numerical values generated by this method can be used to quantitatively determine correlations between the dispersion quality of nanoparticles in polymer-based nanocomposite materials and various macroscale physical and/or performance properties of such materials. This method’s precision was statistically determined to decrease with increasing particle size and be heavily dependent on representative sampling.

Type
Research Article
Copyright
Copyright © Materials Research Society 2011

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References

REFERENCES

1. Allen, T., Particle Size Measurement, Volume 1: Powder sampling and particle size measurement, 5th ed. (Chapman and Hall, New York, 1997).Google Scholar
2. Brewer, Ed and Ramsland, Arnold, Journal of Pharmaceutical Sciences 84 (4), 499 (1995).Google Scholar
3. Gabas, Nadine, Hiquily, Noël, and Laguérie, Claude, Particle and Particle Systems Characterization 11 (2), 121 (1994); Tatsu Nakano and Hiroshi Yuasa, International Journal of Pharmaceutics 215 (1-2), 3 (2001); Hiroshi Yuasa, Tatsu Nakano, and Yoshio Kanaya, International Journal of Pharmaceutics 158 (2), 195 (1997); Hiroshi Yuasa, Tatsu Nakano, and Yoshio Kanaya, International Journal of Pharmaceutics 178 (1), 1 (1999). Google Scholar
4. Boots, B. N., Metallography 15 (1), 53(1982); P. Ganguly and W. J. Poole, Materials Science and Engineering A 332 (1-2), 301 (2002). Google Scholar
5. Wray, P. J., Richmond, O., and Morrison, H. L., Metallography 16 (1), 39 (1983).Google Scholar
6. Karnezis, P. A., Durrant, G., and Cantor, B., Materials Characterization 40 (2), 97 (1998).Google Scholar
7. Underwood, E. E., Quantitative Stereology. (Addison-Wesley, Reading, MA, 1970).Google Scholar
8. Rogers, A., Statistical Analysis of Spatial Dispersions: The Quadrat Method. (Pion, London, 1974).Google Scholar
9. Ripley, B. D., J. R. Stat. Soc. B39, 172 (1977).Google Scholar
10. Silva, N. and Velhinho, A., Materials Science Forum 514516, 779 (2006).Google Scholar