The research reported in this manuscript concerns the structural characterization of graphene membranes and single-walled carbon nanotubes (SWCNTs). The experimental investigation was performed using a wide range of transmission electron microscopy (TEM) techniques, from conventional imaging and diffraction, to advanced interferometric methods, like electron holography and Geometric Phase Analysis (GPA), using a low-voltage optical set-up, to reduce radiation damage in the samples. Electron holography was used to successfully measure the mean electrostatic
potential of an isolated SWCNT and that of a mono-atomically thin graphene crystal. The high accuracy achieved in the phase determination, made it possible to measure, for the first time, the valence-charge redistribution induced by the lattice curvature in an individual SWCNT. A novel methodology for the 3D reconstruction of the waviness of a 2D crystal membrane has been developed. Unlike other available TEM reconstruction techniques, like tomography, this new one requires processing of just a single HREM
micrograph. The modulations of the inter-planar distances in the HREM image are measured using Geometric Phase Analysis, and used to recover the waviness of the crystal. The method was applied to the case of a folded FGC, and a height variation of 0.8 nm of the surface was successfully determined with nanometric lateral resolution. The adhesion of SWCNTs to the surface of graphene was studied, mixing shortened SWCNTs of different chiralities and FGC membranes. The spontaneous atomic match of the two lattices was directly imaged using HREM, and we found that graphene membranes act as tangential nano-sieves, preferentially grafting achiral tubes to their surface.
Identifer | oai:union.ndltd.org:unibo.it/oai:amsdottorato.cib.unibo.it:1612 |
Date | 25 May 2009 |
Creators | Ortolani, Luca <1979> |
Contributors | Morandi, Giuseppe, Lulli, Giorgio |
Publisher | Alma Mater Studiorum - Università di Bologna |
Source Sets | Università di Bologna |
Language | English |
Detected Language | English |
Type | Doctoral Thesis, PeerReviewed |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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