4.6 Article

A self-consistent mean-field model for polyelectrolyte gels

Journal

SOFT MATTER
Volume 13, Issue 18, Pages 3264-3274

Publisher

ROYAL SOC CHEMISTRY
DOI: 10.1039/c6sm02825j

Keywords

-

Funding

  1. Czech Science Foundation [P208/14-23288J]
  2. Ministry of Education, Youth and Sports (CUCAM) [CZ.02.1.01/0.0/0.0/15\_003/0000417]
  3. Marie Curie International Research Staff Exchange Scheme Fellowship 7th European Community Framework Programme [PIRSES-GA-2013612562]
  4. DFG [HO 1108/26-1, AR 593/7-1]
  5. ''Projects of Large Research, Development, and Innovations Infrastructures''
  6. Government of Russian Federation [074-U01]
  7. Russian Foundation of Basic Research [14-03-00372]

Ask authors/readers for more resources

We present a novel approach to modeling polyelectrolyte gels, exploiting the analogy between star-branched polymers and polymer networks as a computationally inexpensive yet reliable alternative to full-scale simulations. In the numerical mean-field model of a star-like polymer we modify the boundary conditions to represent an infinite network. We validate the predictions of our new model against a coarse-grained simulation model. We also validate it against a phenomenological analytical model which has been previously shown to agree with simulations in a limited range of parameters. The mean-field model explicitly considers local density gradients and agrees with the simulation results in a broad range of parameters, beyond that of the analytical model. Finally, we use the mean-field model for predictions of the swelling behaviour of weak polyelectrolyte gels under different pH conditions. We demonstrate that the local density gradients are important and that the ionization of the weak polyelectrolyte gel is significantly suppressed. Under the studied conditions the effective pK(A) is about one unit higher than that of the free monomer. This shift in the effective pK(A) stems from the different pH values inside and outside the gel.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available