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Research Article

Cost effective synthesis of Mn doped NiO/rGO nanocomposite for non-enzymatic electrochemical glucose sensor

, , , , , , & show all
Received 26 Jul 2022, Accepted 13 Sep 2022, Published online: 07 Nov 2022
 

ABSTRACT

Herein, we report the synthesis, characterisation and glucose sensor study of prepared compounds and composite. The prepared samples reported here for glucose-sensing applications were doped (Mn.NiO) and un-doped metal oxide (NiO) and their composite with 2D layered material (Mn-doped-NiO/rGO). The structural analysis of the samples was done by conventional technique called as X-rays diffraction (×RD). Spectral and functional groups’ analysis was elucidated by FTIR spectroscopy. The electron microscopy (SEM) was used for morphological features study. The electrochemical measurements were carried out to analyse biosensing response. Carbon fibre cloth was used as a substrate material to fabricate Mn-doped-NiO/rGO nanocomposite-based biosensor for glucose detection. The analytical performance of the synthesised material was evaluated in terms of electrochemical sensitivity, linear response and limit of detection (LOD). The results showed that the material exhibited an excellent electrochemical sensitivity towards glucose detection with wider range of linear responses. The LOD for Mn-doped-NiO/rGO nanocomposite was 0.11 µM, regression equation for the low concentration was I(µA) = 1477.1C + 165.19 with correlation coefficient value R2 = 0.9849. Conclusively, the rGO-based Mn-doped-NiO nanocomposite experienced robust potential as non-enzymatic sensor for detection of glucose.

Acknowledgements

Authors are thankful to the Institute of Chemistry, The Islamia University of Bahawalpur-Pakistan for providing research facilities. Authors are also thankful to the King Khalid University for grant (KKU/RCAMS/22) under the Research Center for Advanced Materials Science (RCAMS) at King Khalid University, Saudi Arabia.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the King Khalid University [KKU/RCAMS/22].

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