Thermodynamics and structure of self-assembled networks
A.G. Zilman, S.A. Safran

TL;DR
This paper presents a mean-field model of self-assembling branched chains forming networks, revealing entropy-driven phase separation and percolation transitions, with implications for various soft matter systems.
Contribution
It introduces a unified theoretical framework linking thermodynamic phase behavior and connectivity in self-assembled networks, including phase separation and percolation phenomena.
Findings
Entropy of junctions induces effective attraction between monomers.
First-order reentrant phase separation occurs at three-fold junctions.
Percolation transition is continuous and overlaps with phase separation.
Abstract
We study a generic model of self-assembling chains which can branch and form networks with branching points (junctions) of arbitrary functionality. The physical realizations include physical gels, wormlike micells, dipolar fluids and microemulsions. The model maps the partition function of a solution of branched, self-assembling, mutually avoiding clusters onto that of a Heisenberg magnet in the mathematical limit of zero spin components. The model is solved in the mean field approximation. It is found that despite the absence of any specific interaction between the chains, the entropy of the junctions induces an effective attraction between the monomers, which in the case of three-fold junctions leads to a first order reentrant phase separation between a dilute phase consisting mainly of single chains, and a dense network, or two network phases. Independent of the phase separation, we…
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