Defect-controlled softness, diffusive permeability, and mesh-topology of metallo-supramolecular hydrogels

Abstract

Hydrogels are polymer networks swollen in water; they are suitable materials for biomedical applications such as tissue engineering and drug delivery. In the latter, the controlled diffusion of small diffusants inside the network is essential, as it determines the release mechanism of the drug. In general, the diffusion inside a polymer network is controlled by its mesh-size. Here, we actively control the diffusivity and also the softness of metallo-supramolecular hydrogels via the network mesh-topology by introducing connectivity defects. A model polymer network is realized based on a 4-arm poly(ethylene glycol) (pEG) where each arm is capped with terpyridine moieties that are capable of forming metallo-supramolecular complexes with zinc ions. In this model network, we insert 8-arm pEG macromolecules that are functionalized with terpyridine at different ratios to create connectivity defects. With an increasing amount of 8-arm pEG, the polymer network forms more loops, as quantified by double quantum-NMR. This doped network shows an enhanced self-diffusivity of the building block molecules within the network, as examined by fluorescence recovery after photobleaching, and a higher softness, as investigated by oscillatory shear rheology. With these findings, we show that it is possible to tune the diffusivity and softness of hydrogels with defects in a rational fashion.

Graphical abstract: Defect-controlled softness, diffusive permeability, and mesh-topology of metallo-supramolecular hydrogels

Supplementary files

Article information

Article type
Paper
Submitted
09 Oct 2021
Accepted
05 Dec 2021
First published
14 Jan 2022
This article is Open Access
Creative Commons BY license

Soft Matter, 2022, Advance Article

Defect-controlled softness, diffusive permeability, and mesh-topology of metallo-supramolecular hydrogels

P. Nicolella, M. F. Koziol, L. Löser, K. Saalwächter, M. Ahmadi and S. Seiffert, Soft Matter, 2022, Advance Article , DOI: 10.1039/D1SM01456K

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