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Topological nanoinhomogeneities in polymer networks
Author(s) -
Dušek Karel,
Šomvársky Ján
Publication year - 1996
Publication title -
macromolecular symposia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.257
H-Index - 76
eISSN - 1521-3900
pISSN - 1022-1360
DOI - 10.1002/masy.19961060113
Subject(s) - branching (polymer chemistry) , cluster (spacecraft) , topology (electrical circuits) , polymer , statistical physics , percolation (cognitive psychology) , monte carlo method , materials science , chemical physics , physics , computer science , mathematics , combinatorics , statistics , neuroscience , composite material , biology , programming language
Abstract Small‐size topological inhomogeneities in polymer networks characterized by differences in composition are formed as a consequence of history‐determined covalent linking of units differing in some property into chemical clusters (topological inhomogeneities). This process is possibly assisted by physical association (segregation) of units of different types. Evolution of hard clusters in mixtures of long and short chains crosslinked with a common crosslinking agent and multicomponent polyurethane networks have been treated as examples of evolution of topological inhomogeneities. Simple mean‐field models based on the statistical theory of branching processes (TBP) have been developed for modelling of the topological inhomogeneities (molecular weight averages, functionality averages, percolation threshold, etc.) in dependence on initial composition, reactivities of the functional groups, or history of network formation. Such characterization was possible by distinguishing bonds between e.g. soft‐soft, soft‐hard, and hard‐hard units. More sophisticated models view inhomogeneities formation as a kinetic process where effective reactivity of functional groups in reactions, by which inhomogeneities are formed, depends on the size and composition of a given chemical cluster. This model is based on Monte‐Carlo simulations of the generalized Smoluchowski coagulation process.