Topological defects structural properties

Defects in carbon nanostructures can be classified into (a) structural defects, (b) topological defects, (c) high curvature and (d) non-sp2 carbon defects. Even slight changes within the carbon nanostructure can modify the chemical and physical properties. Some defects in carbon systems results in high chemical reactivity, mainly due to the accumulation of electrons in the vicinity of the dopant. These defects can be used as anchoring sites in order to make the carbon nanostructures more compatible with ceramic or polymer matrices, thus enhancing interactions between carbon structures (filler) and the host matrices. 

The molecular chirality and tendency of many liquid crystalline phases (even composed of nonchiral molecules) to twist results in spectacular director configurations that often include topological defects and solitons. We covered the very basic properties of deformations related to twisted structures the considerations were restricted mainly to a uniaxial cholesteric phase in a static regime. Some of the areas where one can expect further exciting progress are listed below. 

Carbon nanotubes have been studied extensively since their discovery [1] in 1991, because of the extraordinary physical properties they exhibit in electronic, mechanical, and thermal processes. A single-walled nanotube may be considered as a specific, one-dimensional giant molecule composed purely of carbon, whereas properties of multiwalled nanotubes are closest to those of graphite s in-plane properties, having sp hybridization of carbon bonds. To prepare closed-shell structures, one needs to insert topological defects into the hexagonal stmcture of graphene sheets. The extraordinary physical and chemical properties [2] and possible applications derived from these properties are attributed to the one-dimensionality and helicity of the nanotube structure. 

The description of a network structure is based on such parameters as chemical crosslink density and functionality, average chain length between crosslinks and length distribution of these chains, concentration of elastically active chains and structural defects like unreacted ends and elastically inactive cycles. However, many properties of a network depend not only on the above-mentioned characteristics but also on the order of the chemical crosslink connection — the network topology. So, the complete description of a network structure should include all these parameters. It is difficult to measure many of these characteristics experimentally and we must have an appropriate theory which could describe all these structural parameters on the basis of a physical model of network formation. At present, there are only two types of theoretical approaches which can describe the growth of network structures up to late post-gel stages of cure. One is based on tree-like models as developed by Dusek7 I0-26,1 The other uses computer-simulation of network structure on a lattice this model was developed by Topolkaraev, Berlin, Oshmyan 9,3l) (a review of the theoretical models may be found in Ref.7) and in this volume by Dusek). Both approaches are statistical and correlate well with experiments 6,7 9 10 13,26,31). They differ mainly mathematically. However, each of them emphasizes some different details of a network structure. 

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