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Carbon Nanotube and Graphene Nanoelectromechanical Systems

Abstract

One-dimensional and two-dimensional forms of carbon are composed of sp2-hybridized carbon atoms arranged in a regular hexagonal, honeycomb lattice. The two-dimension- al form, called graphene, is a single atomic layer of hexagonally-bonded carbon atoms. The one-dimensional form, known as a carbon nanotube, can be conceptualized as a rectangular piece of graphene wrapped into a seamless, high-aspect-ratio cylinder or tube. This dissertation addresses the physics and applied physics of these one and two-dimensional carbon allotropes in nanoelectromechanical systems (NEMS).

First, we give a theoretical background on the electrodynamics and mechanics of carbon nanotube NEMS. We then describe basic experimental techniques, such as electron and scanning probe microscopy, that we then use to probe static and dynamic mechanical and electronic behavior of the carbon nanotube NEMS. For example, we observe and control non-linear beam bending and single-electron quantum tunneling effects in carbon nanotube resonators. We then describe parametric amplification, self-oscillation behavior, and dynamic, non-linear effects in carbon nanotube mechanical resonators. We also report a novel approach to fabricate carbon nanotube atomic force microscopy (AFM) probes, and show that they can lead to exceptional lateral resolution enhancement in AFM when imaging both hard and soft (biological) materials.

Finally, we describe novel fabrication techniques for large-area, suspended graphene membranes, and utilize these membranes as TEM-transparent, AFM-compatible, NEMS resonators. Laser-driven mechanical vibrations of the graphene resonators are detected by optical interferometry and several vibration harmonics are observed. A degeneracy splitting is observed in the vibrational modes of square-geometry resonators. We then attribute the observed degeneracy splitting to local mass inhomogeneities and membrane defects, and find good overall agreement with the developed theoretical model.

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