AVS 53rd International Symposium
    Surface Science Thursday Sessions
       Session SS2+NS+TF-ThA

Paper SS2+NS+TF-ThA8
The Effect of Filling and Temperature on the Mechanical Responses of Carbon Nanotubes

Thursday, November 16, 2006, 4:20 pm, Room 2004

Session: Tribology
Presenter: S.-J. Heo, University of Florida
Authors: S.-J. Heo, University of Florida
S.B. Sinnott, University of Florida
Correspondent: Click to Email
It is well known that carbon nanotubes (CNTs) have fascinating electrical, optical, chemical, and mechanical properties that differ from the properties of macroscale carbon materials such as graphite or diamond. As a result of these properties, CNTs are being considered as candidate materials for MicroElectoMechanical System (MEMS)/NanoElectroMechanical System (NEMS) components. It is therefore worthwhile to study the mechanical behavior of CNTs to better understand how they might fit in with the mechanical property requirements of MEMS/NEMS. To facilitate this better understanding, we have explored two different mechanical responses of CNTs, to bending and compression, using classical molecular dynamics simulations. The second generation reactive bond order potential is used to model the short-range covalent interactions and a Lennard-Jones potential is used to model the long- range van der Waals interactions. In particular, we have modeled a three-point bend test to explore the mechanical responses of the single walls CNTs, single-walled CNTs filled with C60, double-walled CNTs, and triple-walled CNTs. A compression test has also been done on these same systems. Filling the single-walled CNTs, or increasing the number of inner shells in the case of multi-walled CNTs, is predicted to increase both the bending strength and the maximum buckling force. We have also investigated the effect of temperature on the mechanical responses of the CNTs. On the whole, higher temperatures are predicted to lower the bending strength of the CNTs. This work is supported by the National Science Foundation funded Network for Computational Nanotechnology (EEC-02288390).