journal article·2013

One-pot green synthesis, characterizations, and biosensor application of self-assembled reduced graphene oxide–gold nanoparticle hybrid membranes

Panpan Zhang, Xiaoyuan Zhang, Siyu Zhang, Xin Lu, Qing Li, Zhiqiang Su, Gang Wei

Journal of Materials Chemistry B· Volume 1· Issue 47
Publisher page

Abstract

We report here a facile one-pot green synthesis method to prepare a self-assembled membrane of reduced graphene oxide–gold nanoparticle (RGO–AuNP) nanohybrids at a liquid–air interface. The obtained sandwich-like multilayer RGO–AuNP hybrid membranes were characterized by atomic force microscopy, scanning electron microscopy, transmission electron microscopy, UV-vis spectroscopy, Fourier transform infrared spectroscopy, X-ray diffraction, and Raman spectroscopy, and the obtained results prove that GO and chloroauric acid (HAuCl4) were synchronously reduced by glucose successfully. In addition, the experimental data indicate that the self-assembly and formation of RGO–AuNP hybrid membranes are mainly governed by the Brownian motion and electrostatic interaction between RGO and AuNPs, and the encapsulation of AuNPs in the hybrid membrane can be easily adjusted by changing the concentration of HAuCl4. The created functional semi-transparent RGO–AuNP hybrid membranes are very stable in various organic and inorganic solvents, and can be used to fabricate a novel nonenzymatic amperometric biosensor of hydrogen peroxide (H2O2). The fabricated H2O2 biosensor reveals a wide linear range from 0.25 to 22.5 mM, low detection limit of 6.2 μM (S/N = 3), high selectivity, and long-term stability. It is expected that this one-pot green method for fabricating sandwich-like multilayer hybrid functional membranes has broad applications in biosensing, catalysis, and energy storage.
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Research context

OpenAlex topics: Graphene and Nanomaterials Applications · Electrochemical sensors and biosensors · Advanced biosensing and bioanalysis techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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