Effects of Network Chain Length Distribution

Control of Ultimate Properties A. Effects of Network Chain Length Distribution 

PDMS networks, these increases in modulus and ultimate strength are due to the low incidence of dangling-chain irregularities and to non-Gaussian effects arising from limited chain extemibility2 22). 

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Multimodal networks represent a method to determine the effect of network chain-length distribution - on rubberlike elasticity. Chain-length distribution has not received much attention even though manipulation of the chain-length distribution can give large improvements in mechanical properties. There are two primary reasons for this... 

Sun, C.-C. Mark, J. E., The Effect of Network Chain Length Distribution, Specifically Bimodality, on Strain-Induced Crystallization. J. Polym. Sci., Polym. Phys. Ed. 1987,25, 2073-2083. 

Sun C-C, Mark JE. The effect of network chain length distribution, specifically bimodality, on strain-induced crystallization. J Polym Sci Polym Phys Ed 1987 25 2073-83. 

Finally, the possible utilization of model systems in other areas of rubberlike elasticity is illustrated by some brief comments on three important problems of current interest. These are the effects of network chain length distribution on strain-induced crystallization, the properties of networks containing known amounts of well-characterized unattached ( reptating ) chains, and the properties of elastomers consisting of two networks which interpenetrate one another. 

Parallel to the development of the new theoretical approaches considerable experimental work was done on model networks especially synthesized, to show the effects of pendent chains, loops, distribution of chain length, functionality of crosslinks, etc. on properties (5-21). In some instances, the properties turned out... 

This suggests that network chain length distribution had negligible effect on the equilibrium tensile behavior for the range of investigated in this study = 1.1-2.5). 

Strain-induced crystallization would presumably further improve the ultimate properties of a bimodal network. It would therefore obviously be of considerable importance to study the effect of chain length distribution on the ultimate properties of bimodal networks prepared from chains having melting points well above the very low value characteristic of PDMS. Studies of this type are being carried out on bimodal networks of polyethylene oxide) (55), poly(caprolactone) (55), and polyisobutylene (56). 

Falender, J. R. Yeh, G. S. Y. Mark, J. E., The Effect of Chain Length Distribution on Elastomeric Properties. 2. Comparisons Among Networks of Varying Degrees of Randomness. Macromolecules 1979,12,1207-1209. 

Model networks are tridimensional crosslinked polymers whose elastically effective network chains are of known length and of narrow molecular weight distribution. The techniques used to synthesize such networks are derived from those developed for the synthesis of star shaped macromolecules, whereby the initiator used must be bifunctional instead of monofunctional. ... 

The elastically effective network chains should obey Gaussian statistics. They should therefore be long enough, and their average degree of polymerization should be known. In addition the distribution of chain-lengths is expected to be rather narrow. 

Polyurethane Networks. Andrady and Sefcik (1983) have applied the same relationship as Rietsch et al. (1976), to the glass transition temperature of networks based on poly(propylene oxide) diols with a controlled molar mass distribution, crosslinked by aromatic triisocyanates. They obtained a Kr value of 25 K kg mol-1, about twice that for PS networks. They showed that the length distribution of elastically active chain lengths, directly related to the molar mass distribution of the starting poly(propylene oxide), has practically no effect on Tg. 

As normally prepared, molecular networks comprise chains of a wide distribution of molecular lengths. Numerically, small chain lengths tend to predominate. The effect of this diversity on the elastic behavior of networks, particularly under large deformations, is not known. A related problem concerns the elasticity of short chains. They are inevitably non-Gaussian in character and the analysis of their conformational statistics is likely to be difficult. Nevertheless, it seems necessary to carry out this analysis to be able to treat real networks in an appropriate way. 

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