Structure-property correlation maps

Such tests not only provide us with information about the macroscopic properties of the material but also a deeper understanding of its deformation behavior at the micro- and nanoscopic scales. In situ tools allow the local morphology and the deformation in a material that is subjected to local mechanical stresses to be mapped out. Therefore, these studies open up a very direct way to determine structure-property correlations of polymers and to explain them on the basis of nano- and micromechanical mechanisms in dependence on real morphology [2],... 

Exploratory analysis of spectral data by PCA, PLS, cluster analysis, or Kohonen mapping tries to get an insight into the spectral data structure and into hidden factors, as well as to find clusters of similar spectra that can be interpreted in terms of similar chemical structures. Classification methods, such as LDA. PLS, SIMCA, KNN classification, and neural networks, have been used to generate spectral classifiers for an automatic recognition of structural properties from spectral data. The multivariate methods mostly used for spectra prediction (mainly NMR. rarely IR) are neural networks. Table 6 contains a summary of recent works in this field (see Infrared Data Correlations with Chemical Structure). 

For iron-carbon alloys, in addition to discussions of the heat treatments that produce the several microconstituents (fine/coarse pearlite, bainite, martensite, etc.) and their mechanical properties, correlations were made between mechanical properties and structural elements of these microconstituents. These correlations are indicated in the following concept map ... 

Processing/Structure/Properties/Performance correlations and summary concept maps for four materials (steels, glass-ceramics, polymer fibers, and silicon semiconductors), which integrate important concepts from chapter to chapter... 

Alternatively, calculated molecular properties from 3D molecular fields of interaction energies represent a valuable approach to correlate 3 D molecular structures with physicochemical and pharmacodynamic properties. In contrast, their use in correlations with pharmacokinetic properties is still poorly explored and exploited. The rather new VolSurf approach [5-7] is able to compress the relevant information present in 3D maps into a few descriptors characterized by the simplicity of... 

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