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Three-Dimensional Representation of Curved Nanostructures

Published online by Cambridge University Press:  15 March 2011

Z. Huang
Affiliation:
Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208, USA
D.A. Dikin
Affiliation:
Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208, USA
W. Ding
Affiliation:
Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208, USA
Y. Qiao
Affiliation:
Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208, USA
Y. Fridman
Affiliation:
Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA
R.S. Ruoff
Affiliation:
Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208, USA
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Abstract

Nanostructures, such as nanowires, nanotubes, and nanocoils, can be described in many cases as quasi one-dimensional (1D) curved objects projecting in three-dimensional (3D) space. A parallax method to reconstruct the correct three-dimensional geometry of such 1D nanostructures is presented. A series of images were acquired at different view angles, and from those image pairs, 3D representations were constructed using a MATLAB program. Error analysis as a function of view-angle between the two images is discussed. As an example application, we demonstrate the importance of knowing the true 3D shape of Boron nanowires. Without precise knowledge of the nanowire's dimensions, diameter and length, mechanical resonance data cannot be properly fit to obtain an accurate estimate of the Young's modulus.

Type
Research Article
Copyright
Copyright © Materials Research Society 2004

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References

1. Treacy, M.M.J., Ebbesen, T.W. and Gibson, J.M., Nature, 381, 678 (1996).Google Scholar
2. Poncharal, P., Wang, Z.L., Ugarte, D. and Heer, W.A. de, Science, 283, 1513 (1999).Google Scholar
3. Yu, M-F, Wagner, G.J., Ruoff, R.S. and Dyer, M.J., Phys. Rev. B, 66, 073406 (1-4) (2002).Google Scholar
4. Dikin, D.A., Chen, X., Ding, W., Wagner, G. and Ruoff, R.S., J. Appl. Phys., 93, 226 (2003).Google Scholar
5. Boyde, A., J. Microsc. 98, 452 (1973).Google Scholar
6. Thong, J.T.L. and Breton, B.C., Rev. Sci. Instrum. 63(1), 131 (1992)Google Scholar
7. Hein, L.R.O., Silva, F.A., Nazar, A.M.M. and Amann, J.J., Scanning, 21, 253 (1999).Google Scholar
8. Cheng, Y., Hartemink, C.A., Hartwig, J.H. and Dewey, C.F., J. Biomech., 33, 105 (2000).Google Scholar
9. Hein, L.R.O., J. Microsc., 204, 17 (2001).Google Scholar
10. Hartley, R. and Zisserman, A., Multiple view geometry in computer vision, (Cambridge University Press, 2000) p. 607.Google Scholar
11. Henri, C.J., and Peter, T.M., Med. Phys., 23(2), 197 (1996).Google Scholar
12. Bullitt, E., Liu, A. and Pizer, S.M., Med. Phys., 24(11), 1671 (1997).Google Scholar
13. Dikin, D.A., Huang, Z. and Ruoff, R.S., submitted to Rev. Sci. Instrum. (2004)Google Scholar
14. Fridman, Y., Pizer, S.M., Aylward, S. and Bullitt, E. in Medical Image Computing and Computer-Assisted Intervention, (MICCAI 2003 Proc., Montréal, Canada) pp. 570577.Google Scholar