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Three-dimensional molecular geometry of PEG hydrogels by an “expansion-contraction” method through Monte Carlo simulations

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Abstract

Three-dimensional (3-D) coarse-grained Monte Carlo algorithms were used to simulate the conformations of swollen hydrogels formed by copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC). The simulation consists of three successive steps including diffusion, cross-linking and relaxation. The cross-linking of multifunctional reaction sites is simulated instantly followed by fast crosslinking. In order to explore the validity of this approach pristine poly(ethylene glycol) (PEG) hydrogels with tri- and tetra-functional reaction sites (G3 and G4 respectively) were prepared and characterized. The data from the simulations were found to be in good agreement with experimental results such as PEG lengths between crosslinks, pore volume and pore radius distribution, indicating the validity of the modeling algorithm. The calculated PEG lengths in G3 and G4 networks are close (≈ 4.6 nm). The 3-D visual topological structure of the hydrogel network suggests that the “ideal” hydrogel is far from cubic, diamond or any well defined structures of regular repeating cells.

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Authors and Affiliations

  1. School of Chemistry and Chemical Engineering, Southeast University, Jiangning District, Nanjing, 211189, China

    Ao-kai Zhang, Yu-wei Sun & Guo-dong Fu  (付国东)

  2. Department of Polymer Science and Engineering, Zhejiang University, Hangzhou, 310027, China

    Jun Ling  (凌君)

Authors
  1. Ao-kai Zhang
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  2. Jun Ling  (凌君)
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  3. Yu-wei Sun
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  4. Guo-dong Fu  (付国东)
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Corresponding authors

Correspondence to Jun Ling  (凌君) or Guo-dong Fu  (付国东).

Additional information

This work was financially supported by the National Natural Science Foundation of China (Nos. 21274020, 21074022 and 21304019) and Zhejiang Provincial Natural Science Foundation of China (No. Y4110115).

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Zhang, Ak., Ling, J., Sun, Yw. et al. Three-dimensional molecular geometry of PEG hydrogels by an “expansion-contraction” method through Monte Carlo simulations. Chin J Polym Sci 33, 721–731 (2015). https://doi.org/10.1007/s10118-015-1620-4

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  • DOI: https://doi.org/10.1007/s10118-015-1620-4

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