The properties and function of supramolecular polymer networks are determined not only by pairwise interchain transient associations but also by chain entanglement and nanoscopic phase separation of the associative groups. To unravel the impact and interplay of these different factors, we devise a set of model supramolecular polymer networks in which the number of entanglements and the density of associative groups are systematically varied. Rheological data show that by increasing the density of associative groups, the plateau modulus grows to a steady level and extends over a distinct frequency range. This is credited to the presence of binary associations with unique partner exchange time. For samples where the high-frequency plateau stays at the constant level, a second plateau emerges at low frequencies in addition. This plateau, which is well below the entanglement plateau of the precursor, is attributed to the presence of collective assemblies of nanophase-separated associative groups, as confirmed by FTIR spectroscopy. The contributions of these two different levels of interchain associations are decoupled on the basis of a tube-based model. The obtained model parameters show that by increasing the number of network junctions, including both interchain associations and entanglements, the fraction of binary associations decreases, while the density of collective ones approaches a constant level.

In this review, the origin of clusters in supramolecular polymer materials, their characterization, their effects on the dynamic and mechanical properties, and their potentials for designing functional materials are overviewed.

The dynamic mechanical properties of supramolecular associative polymer networks depend on the average number of entanglements along the network-forming chains, N e , and on their content of associative groups, f. In addition, there may be further influence by aggregation of the associative groups into clusters, which, in turn, is influenced by the chemical structure of these groups, and again by N e and f of the polymer. Therefore, the effects of these parameters are interdependent. To conceptually understand this interdependency, we study model networks in which (a) N e , (b) f, and (c) the chemical structure of the associative groups are varied systematically. Each network is probed by rheology. The clustering of the associative groups is assessed by analyzing the rheological data at the end range of frequency covered and by comparison of the number of supramolecular network junctions with the maximum possible number of binary transient bonds. We find that if the total number of the network junctions, which can be formed either by interchain entanglement or by interchain transient associations, is greater than a threshold of 13, then the likelihood of cluster formation is high and the dynamics of supramolecular associative polymer networks is mainly controlled by this phenomenon.