Literature DB >> 32228941

Morphology-dependent MnO2/nitrogen-doped graphene nanocomposites for simultaneous detection of trace dopamine and uric acid.

Qing Li1, Yonghui Xia2, Xuan Wan1, Shihui Yang1, Zhaotian Cai1, Yabing Ye1, Guangli Li3.   

Abstract

Four nanostructured MnO2 with various controllable morphologies, including nanowires, nanorods, nanotubes and nanoflowers were synthesized, and then further composited with nitrogen-doped graphene (NG) with the assistance of ultrasonication. The surface morphologies, phase structures, and electrochemical performances of the proposed MnO2/NG nanohybrids were investigated by various techniques, and their catalytic activities on the electrooxidation of dopamine (DA) and uric acid (UA) were compared systematically. The sensing performances were found to be highly correlated with their morphologies. Among these morphologies, the nanoflower-like MnO2, composited with NG, displayed the most sensitive response signals for DA and UA. The boosted electrocatalytic activity was ascribed to the unique porous structure, large electroactive area, and low charge transfer resistance (Rct), which facilitated the electron transfer between electrode and analytes. Two linear response ranges (0.1 μM-10 μM and 10 μM-100 μM) were accompanied with very low detection limits of 34 nM and 39 nM for DA and UA, respectively. Moreover, the successful application of the MnO2NFs/NG composites for the simultaneous detection of DA and UA in human serum was realized using second-derivative linear sweep voltammetry (SDLSV). These findings give valuable insights for understanding the morphology-dependent sensing properties of MnO2 based nanomaterials, which is conducive to the rapid development of ubiquitous MnO2-based electrochemical sensors.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Dopamine; Manganese dioxide; Morphology-dependent; Nitrogen-doped graphene; Uric acid

Mesh:

Substances:

Year:  2019        PMID: 32228941     DOI: 10.1016/j.msec.2019.110615

Source DB:  PubMed          Journal:  Mater Sci Eng C Mater Biol Appl        ISSN: 0928-4931            Impact factor:   7.328


  11 in total

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