Issue 8, 2020

Multi-triggered and enzyme-mimicking graphene oxide/polyvinyl alcohol/G-quartet supramolecular hydrogels

Abstract

Supramolecular hydrogels with stimuli-responsive behaviors under aqueous environments are attractive for their potential applications in controlled drug delivery, clinical diagnostics, and tissue engineering. However, there still remain challenges in developing multicomponent hydrogels as a new generation of “smart” soft materials with multiple intelligent functions toward complex biochemical stimuli. In this work, a three dimensional (3D)-nanostructured supramolecular hydrogel was fabricated using a simple and facile strategy via the self-assembly of graphene oxide (GO) nanosheets, poly(vinyl alcohol) (PVA) chains, and G-quartet/hemin (G4/H) motifs. The as-prepared GO/PVA/G4/H hydrogel exhibited a honeycomb-like 3D GO network architecture as well as excellent mechanical properties. Importantly, the hydrogel demonstrated pH-inducing reversible and cyclic phase transitions between solution and hydrogel states, which could be used as “ink” for injectable 3D printing of different shaped patterns. Also, binary AND and OR logic gates were successfully built by encapsulating enzymes into the hydrogels, which responded to a variety of biochemicals. In addition, the hydrogels showed excellent peroxidase-like activity, achieving the ultrasensitive detection of H2O2 at a concentration as low as 100 nM by their deposition on an electrochemical electrode. The design of multicomponent hydrogels opens up an avenue to fabricate novel “smart” soft matter for biological and medical applications.

Graphical abstract: Multi-triggered and enzyme-mimicking graphene oxide/polyvinyl alcohol/G-quartet supramolecular hydrogels

Supplementary files

Article information

Article type
Paper
Submitted
23 Dec 2019
Accepted
16 Jan 2020
First published
27 Jan 2020

Nanoscale, 2020,12, 5186-5195

Multi-triggered and enzyme-mimicking graphene oxide/polyvinyl alcohol/G-quartet supramolecular hydrogels

J. Zhang, N. Lu, H. Peng, J. Li, R. Yan, X. Shi, P. Ma, M. Lv, L. Wang, Z. Tang and M. Zhang, Nanoscale, 2020, 12, 5186 DOI: 10.1039/C9NR10779G

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