On the shape of Gaussian scale-free polymer networks

Fuente: arXiv
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Main Authors: Blavatska, V., Holovatch, Yu.
Format: Preprint
Published: 2024
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author Blavatska, V.
Holovatch, Yu.
author_facet Blavatska, V.
Holovatch, Yu.
contents We consider the model of complex hyperbranched polymer structures formed on the basis of scale-free graphs, where functionalities (degrees) $k$ of nodes obey a power law decaying probability $p(k)\sim{k^{-α}}$. Such polymer topologies can be considered as generalization of regular hierarchical dendrimer structures with fixed functionalities. The conformational size and shape characteristics, such as averaged asphericity $\langle A_3 \rangle$ and size ratio $g$ of such polymer networks are obtained numerically by application of Wei's method, which defines the configurations of any complex Gaussian network in terms of eigenvalue spectra of corresponding Kirchhoff matrix. Our quantitative results indicate, in particular, an increase of compactness and symmetry of network structures with the decrease of parameter $α$.
format Preprint
id arxiv_https___arxiv_org_abs_2411_02566
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On the shape of Gaussian scale-free polymer networks
Blavatska, V.
Holovatch, Yu.
Soft Condensed Matter
Disordered Systems and Neural Networks
We consider the model of complex hyperbranched polymer structures formed on the basis of scale-free graphs, where functionalities (degrees) $k$ of nodes obey a power law decaying probability $p(k)\sim{k^{-α}}$. Such polymer topologies can be considered as generalization of regular hierarchical dendrimer structures with fixed functionalities. The conformational size and shape characteristics, such as averaged asphericity $\langle A_3 \rangle$ and size ratio $g$ of such polymer networks are obtained numerically by application of Wei's method, which defines the configurations of any complex Gaussian network in terms of eigenvalue spectra of corresponding Kirchhoff matrix. Our quantitative results indicate, in particular, an increase of compactness and symmetry of network structures with the decrease of parameter $α$.
title On the shape of Gaussian scale-free polymer networks
topic Soft Condensed Matter
Disordered Systems and Neural Networks
url https://arxiv.org/abs/2411.02566