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Multi-Million Fully Atomistic Molecular Dynamics Simulations of Yarn Formation from Carbon Nanotube Forests

Published online by Cambridge University Press:  12 April 2012

Leonardo D. Machado
Affiliation:
Applied Physics Department, State University of Campinas, Campinas-SP, 13083-459, Brazil.
Sergio B. Legoas
Affiliation:
Physics Department, Federal University of Roraima, Boa Vista-RR, 69304-000, Brazil.
Douglas S. Galvão
Affiliation:
Applied Physics Department, State University of Campinas, Campinas-SP, 13083-459, Brazil.
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Abstract

In this work we present preliminary results from multi-million fully atomistic classical molecular dynamics simulations carried out to test different existing mechanisms that have been proposed in the literature to explain the drawing of yarns from carbon nanotube forests. Despite the fact that it has been almost ten years since yarns were first drawn, there are still controversies on the mechanisms and necessary conditions that can produce yarns and sheets drawn from carbon nanotube forests. Moreover, few works have tried to understand at atomistic level the details of yarn drawing mechanisms, and no fully atomistic simulations have been carried out so far on this particular subject. Our preliminary results suggest that only direct van der Waals interactions among large bundles seem not to be enough to explain the yarn drawing process. Bundle interconnectors (such as small bundles connecting large bundles) were observed to play a critical role in our simulations. Depending on the topology of these interconnectors it was possible to observe from the simulations fibers/yarn formation from proposed structural models. These models were built based on structural information inferred from scanning electron microscopy data.

Type
Research Article
Copyright
Copyright © Materials Research Society 2012

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References

REFERENCES

1. Jiang, K., Li, Q. and Fan, S., Nature 419, 801 (2002).Google Scholar
2. Zhu, C. et al. ., Carbon 49, 4996 (2011).Google Scholar
3. Zhang, M., Atkinson, K. R. and Baughman, R. H., Science 306, 1358 (2004).Google Scholar
4. Zhang, M. et al. ., Science 309, 1215 (2005).Google Scholar
5. Lima, M. D. et al. ., Science 331, 51 (2011).Google Scholar
6. Foroughi, J. et al. ., Science 334, 494 (2011).Google Scholar
7. Lee, I. H. et al. ., ACS Nano 5, 31 (2010).Google Scholar
8. Kuznetsov, A. A. et al. ., ACS Nano 5, 985 (2011).Google Scholar
9. Liu, K. et al. ., Nano Lett. 8, 700 (2008).Google Scholar
10. Huynh, C. P. and Hawkins, S. C., Carbon 48, 1105 (2010).Google Scholar
11. Li, Q. et al. ., Adv. Mater. 18, 3160 (2006).Google Scholar
12. Gilvaei, A. F., Hirahara, K., Nakayama, Y., Carbon 49, 4928 (2011).Google Scholar
13. Zhang, X. et al. ., Adv. Mater. 18, 1505 (2006).Google Scholar
14. Phillips, J. C. et al. ., J. Comput. Chem. 26, 1781 (2005).Google Scholar