Nanostructure topology

The CDF interpretation results in a detailed, yet only qualitative description of the complex nanostructure at each stage of the straining experiment. Several features are frequently superimposed, and the quantitative analysis requires a complex three-dimensional (3D) adapted model to be fitted to the CDF in order to retrieve precise data concerning the nanostructure evolution. For this reason, it may be reasonable to quantitatively study only a partial aspect of the nanostructure topology [23]. 

For anisotropic samples, such as thermoplastic elastomers showing uniaxial orientation, the analysis of the longitudinal structure gives only a fraction of the total information concerning the nanostructure topology. By analogy with the IDF concept, the complete information should be displayed in a multidimensional function that maps the distances between all the domain surfaces. 

The first step in structure parameter determination is the interpretation of the obvious features in the real-space representation of the nanostructure topology. This interpretation leads to a qualitative model describing the nanostructure. Based on this description, a mathematical model may be set up and fitted to the data. Such fitting can be sometimes replaced by the direct determination of parameters of physical meaning. An example concerning the analysis of the transverse structure is presented in the sequel. 

West, R., Y. Wang, and T. Goodson. 2003. Nonlinear absorption properties in novel gold nanostructured topologies. J. Phys. Chem. B 107 (15) 3419-3426. 

In Q the non-topological structure parameters of the material s nanostructure are combined. For multiphase systems this fact can be deduced by application of the Fourier-slice theorem and the considerations which lead to Porod s law. In particular, for a two-phase system it follows64... 

Automated Extraction of Interference Functions. For the classical synthetic polymer materials it is, in general, possible to strip the interference function from the scattering data by an algorithm that does not require user intervention. Quantitative information on the non-topological parameters is lost (Stribeck [26,153]). The method is particularly useful if extensive data sets from time-resolved experiments of nanostructure evolution must be processed. Background ideas and references are presented in the sequel. 

Opportunities and Limits. If we intend to obtain a clearer look on nanostructure than the one the CLD is able to offer, we can try to get rid of the orientation smearing - either by considering materials with a special topology (layer stacks), or by studying anisotropic materials. 

In practical application to common isotropic polymer materials the IDF frequently exhibits very broad distributions of domain thicknesses. At the same time fits of the IDF curve to the well-known models for the arrangement of domains (cf. Sect. 8.7) are not satisfactory, indicating that the existing nanostructure is more complex. In this case one may either tit a more complex model85 on the expense of significance, or one may switch to the study of anisotropic materials and display their nanostructure in a multidimensional representation, the multidimensional CDF. Complex domain topology is more clearly displayed in the CDF than in the IDF. The CDF method is presented in Sect. 8.5.5. 

The analytical structural model for the topology of the nanostructure is defined in Isr (5). For many imaginable topologies such models can be derived by application of scattering theory. Several publications consider layer topologies [9,84,231] and structural entities built from cylindrical particles [240,241], In the following sections let us demonstrate the principle procedure by means of a typical study [84],... 

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. 

Self-assembly is a particular powerful tool in synthesising up large scale nanostructures are topologically complex molecules such as molecular machines and topologically interlocked species. 

These seven italicized criteria are integrated into a variety of (GDS) schemes thus allowing construction of hyperbranched macromolecular structures referred to as dendrons or dendrimers . A direct consequence of this strategy is a systematic molecular morphogenesis [1] with an opportunity to control "critical molecular design parameters (CMDP s) (i.e., size, shape, surface chemistry, topology and flexibility) as one advances with covalent connectivity from molecular reference points (seeds) of picoscopic/sub-nanoscopic size (i.e.. 0.01-1.0 nm) to precise macromolecular structures of nanoscopic dimensions (i.e., 1.0-100 nm) [2]. Genealogically directed synthesis offers a broad and versatile approach to the construction of precise, abiotic nanostructures with predictable sizes, shapes and surface chemistries. 

The electrostatic attraction between oppositely charged molecules is an adjustable driving force for structured material construction. The current synthetic routes of polymer production often offer many variations in size, topology, functionality and polydispersity. An electrostatically driven assembly of nanostructures allows for the controlled incorporation of materials available by synthetic routes. Biological macromolecules, nevertheless, offer superior polyfunctionality compared to synthetic macromolecules. We preferentially use them. 

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