A mesoporous silver-doped TiO2-SnO2 nanocomposite on g-C3N4 nanosheets and decorated with a hierarchical core-shell metal-organic framework for simultaneous voltammetric determination of ascorbic acid, dopamine and uric acid.
Srinivasan KrishnanLiangyu TongShanhu LiuRuimin XingPublished in: Mikrochimica acta (2020)
An electrochemical sensor is described for the simultaneous voltammetric determination of ascorbic acid (AA), dopamine (DA), and uric acid (UA). An indium-tin oxide (ITO) electrode was modified with a hierarchical core-shell metal-organic framework and Ag-doped mesoporous metal-oxide based hybrid nanocomposites on g-C3N4 nanosheets. The morphology, structural and chemical composition of the hybrid nanocomposite was characterized using different analytical methods. The modified ITO showed superior electrocatalytic performance towards the oxidation of AA, DA and UA due to the enhanced surface area, synergistic effects and well-organized porous assembly. Figures of merit, include (a) linear responses from 0.1 to 200 μM, 2.5 to 100 μM and 2.5 to 625 μM; (b) detection limits (at S/N = 3) of 0.02, 0.01 and 0.06 μM, and (c) well separated oxidation peaks near -50, 186 and 390 mV (vs. Ag/AgCl) for simultaneous sensing AA, DA and UA, respectively. The sensor was evaluated by analysing spiked serum samples and gave data with precision, with recoveries of >98%. Graphical abstractSchematic Representation of a Mesoporous Silver-doped TiO2-SnO2 Nanocomposite (h-ATS) on g-C3N4 Nanosheets and Decorated with a Hierarchical Core-Shell Metal-Organic Framework (NC@GC) Based Electrochemical Sensor for Simultaneous Voltammetric Detection of Ascorbic acid, Dopamine and Uric acid.
Keyphrases
- metal organic framework
- uric acid
- reduced graphene oxide
- gold nanoparticles
- visible light
- quantum dots
- metabolic syndrome
- molecularly imprinted
- label free
- loop mediated isothermal amplification
- hydrogen peroxide
- real time pcr
- highly efficient
- drug delivery
- carbon nanotubes
- electronic health record
- sensitive detection
- machine learning
- big data
- cancer therapy
- nitric oxide
- mass spectrometry
- simultaneous determination
- silver nanoparticles
- liquid chromatography
- deep learning
- oxide nanoparticles