Novel neuron-network-like Cu-MoO2/C composite derived from bimetallic organic framework for highly efficient detection of hydrogen peroxide

ABSTRACT Fabrication of non-enzymatic electrochemical sensors based on metal oxides with low valence-state for nanomolar detection of H2O2 has been a great challenge. In this work, a novel neuron-network-like Cu-MoO2/C hierarchical structure was simply prepared by in-situ pyrolysis of 3D bimetallic-organic framework [Cu(Mo2O7)L]n [L: N-(pyridin-3-ylmethyl)pyridine-2-amine] crystals. Meanwhile, the MoO2/C nano-aggregates were also obtained by liquid phase copper etching. Subsequently, two non-enzymatic electrochemical sensors were fabricated by simple drop-coating of the above two materials on the surface of glassy carbon electrode (GCE). Electrochemical measurements indicate that the Cu-MoO2/C/GCE possesses highly efficient electrocatalytic H2O2 property during wider linear range of 0.24 μM∼3.27 mM. At room temperature, the Cu-MoO2/C composite displays higher sensitivity (233.4 μA·mM-1·cm-2) and lower limit of detection (LOD = 85 nM), which are 1 and 2.5 times larger than those of MoO2/C material, respectively. Such excellent ability for trace H2O2 detection mainly originates from the synergism of neuron-network-like structure, enhanced electrical conductivity and increased active sites caused by low valence-state MoO2 and co-doping of Cu and carbon, and even the interaction between Cu and Mo. In addition, the H2O2 detection in spiked human serum and commercially real samples indicates that the Cu-MoO2/C/GCE sensor has certain potential application in the fields of environment and biology.