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Phase equilibria in multicomponent polymer mixtures

✍ Scribed by Onclin, M. H. ;Kleintjens, L. A. ;Koningsveld, R.


Publisher
Wiley (John Wiley & Sons)
Year
1979
Weight
746 KB
Volume
3
Category
Article
ISSN
0025-116X

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✦ Synopsis


In recent years thermodynamic equilibrium properties of amorphous polymer blends have been the subject of increasing interest. Experimental techniques, known in the study of polymer solutions, have been applied to blends and have been modified to deal with highly viscous systems. Determination of Critical points, spinodal and cloud-point curves are now well possible by means of a low-speed centrifuge, pulse induced critical scattering and the centrifugal homogenizer .

The classic Flory-Huggins model cannot describe the experimental results. Improvements can be made by the introduction of the contact Surface areas of the segments, and by correcting the combinatorial entropy of mixing for orientational effects related to chain flexibility. Two-peaked spinodals may furthermore be described with a model accounting for three concentration ranges in the blend, the two dilute solutions of one polymer in the other and an intermediate range of uniform segment density. A s a third possibility the introduction of holes in the lattice (simple lattice gas) can also lead to qualitatively correct descriptions, even in those cases where the phase diagram is still more complex (system poly(styrene-co-acrylonitrile)/ polymethylmethacrylate) and shows three miscibility gaps.

Strictly-binary polymer mixtures with a bimodal cloud-point curve should show two stable critical points. The fact that we did not find more than one may be attributed to polydispersity which easily shifts one of the critical points into the experimentally inaccessible meta-stable region.


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## Abstract Theoretical models describing the dynamics of multicomponent polymer mixtures are reviewed. Some detailed derivations are shown to make the basic assumptions clear and to ease the comparison between these models. The effects of random noise and memory functions on the time evolution of