On the shape of Gaussian scale-free polymer networks
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866916949379776512 |
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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 |
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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 |