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    Fabrication of selective l-glutamic acid sensor in electrochemical technique from wet-chemically prepared RuO2 doped ZnO nanoparticles

    Access Status
    Fulltext not available
    Authors
    Alam, M.M.
    Uddin, M.T.
    Asiri, A.M.
    Awual, Rabiul
    Fazal, M.A.
    Rahman, M.M.
    Islam, M.A.
    Date
    2020
    Type
    Journal Article
    
    Metadata
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    Citation
    Alam, M.M. and Uddin, M.T. and Asiri, A.M. and Awual, M.R. and Fazal, M.A. and Rahman, M.M. and Islam, M.A. 2020. Fabrication of selective l-glutamic acid sensor in electrochemical technique from wet-chemically prepared RuO2 doped ZnO nanoparticles . Materials Chemistry and Physics. 251: Article No. 123029.
    Source Title
    Materials Chemistry and Physics
    DOI
    10.1016/j.matchemphys.2020.123029
    ISSN
    0254-0584
    Faculty
    Faculty of Science and Engineering
    School
    WASM: Minerals, Energy and Chemical Engineering
    URI
    http://hdl.handle.net/20.500.11937/88608
    Collection
    • Curtin Research Publications
    Abstract

    In this approach, RuO2 doped ZnO nanoparticles (NPs; 10% RuO2 doping) were prepared by wet-chemical method and characterized by powder X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Energy-dispersive X-ray spectroscopy (EDS), and Field Emission Scanning Electron Microscopy (FESEM). The slurry of RuO2-doped ZnO NPs in ethanol was deposited as thin film of onto a glassy carbon electrode (GCE) to result in a working electrode to be used for L-glutamic acid (L-GA) sensing probe. The electrochemical response of the sensor was found to be linear in the range of 0.1 nM–0.01 mM in current versus logarithm of concentration plot, called ‘linear dynamic range (LDR)’. The sensitivity of the electrode is found to be 5.42 μAμM−1cm−2. The detection limit is estimated to be 96.0 ± 5.0 pM by using signal-noise ratio of 3. The proposed L-GA sensor has shown excellent reproducibility, good stability and fast response time. It is successfully used to analyze the selective biological sample with the RuO2-doped ZnO nanoparticles fabricated sensor matrix. Thus, this methodology for developing enzyme-less sensor would be the most reliable, efficient, and simple route in the field of healthcare sector in broad scales.

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