MnSe-loaded g-C3N4 nanocomposite with synergistic peroxidase-like catalysis: Synthesis and application toward colorimetric biosensing of H2O2 and glucose

Manganese selenide (MnSe) nanoparticles as nanocatalysts may present enhanced peroxidase-like catalysis if loaded on conductive graphite carbon nitride ( g-C3N4) supports. In this work, MnSe nanoparticles were successfully loaded on the surface of polymeric g-C3N4 as a cocatalyst through a thermal condensation method by calcinating the mixture of pure MnSe, dicyandiamide and cyanuric acid. The morphology and composition of thus-prepared MnSe loaded doped graphite phase carbon nitride nanosheets (MnSe-g-C3N4) were characterized by transmission electron microscopy (TEM), high resolution TEM, X-ray diffraction (XRD), Fourier transform infrared (FT-IR) spectra and X-ray photoelectron spectroscopy (XPS). Structural analyses revealed that the MnSe-g-C3N4 nanoparticles are composed of ultrathin nanosheets with 20 nm lateral diameter. Compared with original MnSe and g-C3N4, the prepared MnSe-g-C3N4 nanosheets could achieve higher aqueous stability and, especially, much stronger peroxidase-like catalysis, presumably resulting from the synergetic effects of conductive carbon nitride and lamellate MnSe nanocatalysts effectively loaded. Significantly, MnSe-g-C3N4 nanosheets were proved to be novel peroxidase mimetics which could quickly catalyze oxidation of the peroxidase substrate 3,3',5,5'-tetramethylbenzidine (TMB) in the presence of H2O2, producing a blue colored solution. Kinetic analysis indicates that the catalytic behavior satisfy typical Michaelis-Menten kinetics and follows a ping-pong mechanism. Colorimetric detections of H2O2 and glucose using the MnSe-g-C3N4 nanosheets were conducted with high detection sensitivities, demonstrating the feasibility of practical sensing applications. It is therefore believed that our findings in this study could open up the possibility of utilizing MnSe-g-C3N4 nanosheets as enzymatic mimics in diagnostics and biotechnology fields. (C) 2016 Published by Elsevier B.V.