Marginally compact hyperbranched polymer trees

Assuming Gaussian chain statistics along the chain contour, we generate by means of a proper fractal generator hyperbranched polymer trees which are marginally compact. Static and dynamical properties, such as the radial intrachain pair density distribution ρ pair ( r ) or the shear-stress relaxatio...

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Bibliographic Details
Published in:Soft matter 2017-03, Vol.13 (13), p.2499-2512
Main Authors: Dolgushev, M, Wittmer, J. P, Johner, A, Benzerara, O, Meyer, H, Baschnagel, J
Format: Article
Language:English
Subjects:
Chains (polymeric)
Condensed Matter
Density
Fractal analysis
Physics
Shape
Spacers
Statistics
Trees
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Summary:Assuming Gaussian chain statistics along the chain contour, we generate by means of a proper fractal generator hyperbranched polymer trees which are marginally compact. Static and dynamical properties, such as the radial intrachain pair density distribution ρ pair ( r ) or the shear-stress relaxation modulus G ( t ), are investigated theoretically and by means of computer simulations. We emphasize that albeit the self-contact density diverges logarithmically with the total mass N , this effect becomes rapidly irrelevant with increasing spacer length S . In addition to this it is seen that the standard Rouse analysis must necessarily become inappropriate for compact objects for which the relaxation time τ p of mode p must scale as τ p ∼ ( N / p ) 5/3 rather than the usual square power law for linear chains. We generate by means of a proper fractal generator hyperbranched polymer trees which are marginally compact. It is shown that the logarithmical divergence of the self-contact density with the total mass becomes rapidly irrelevant with increasing spacer length.
ISSN:1744-683X
1744-6848
DOI:10.1039/c7sm00243b