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Ethylene glycol-sensing properties of hydrothermally grown feather-like ZnO nanopowder with abundant oxygen vacancies

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Abstract

The hydrothermal method was used to prepare feather-like ZnO nanopowder for sensing application. The morphological and structural properties have been investigated through X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), Fourier transform infrared spectroscopy (FTIR), energy-dispersive X-ray spectroscopy (EDX), X-ray photoelectron spectroscopy (XPS), and photoluminescence spectroscopy (PL). The abundance of oxygen vacancy was directly confirmed through the XPS and PL data and was implicitly approved by the resistance variations as a function of the temperature. The gas-sensing features were examined toward methanol, isopropanol, dimethylformamide, acetone, ethanol, and ethylene glycol vapors. The results showed that this sample has a very good selectivity to ethylene glycol (about 4–7 times more than other vapors). The best operating temperature, dynamic response, sensitivity, response/recovery times, and the detection limit of the sample were studied. The effect of the humidity on the performance of the sensor was also investigated.

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Acknowledgments

We would like to thank Prof. Emil J. W. List-Kratochvil and Dr. Giovanni Ligorio from Humboldt University of Berlin for their support in XPS analysis.

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Authors and Affiliations

  1. Department of Solid State Physics, University of Mazandaran, Babolsar, 4741695447, Iran

    Somayeh Saadat Niavol & Hossain Milani Moghaddam

  2. Nano Research Lab, Lahijan Branch, Islamic Azad University, P.O. Box 1616, Lahijan, Iran

    Somayeh Saadat Niavol & Abbas Bagheri Khatibani

  3. Department of Chemistry, Shahid Rajaee Teacher Training University, P.O. Box 16785-163, Tehran, Iran

    Shayesteh Imani

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  1. Somayeh Saadat Niavol
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Saadat Niavol, S., Bagheri Khatibani, A., Imani, S. et al. Ethylene glycol-sensing properties of hydrothermally grown feather-like ZnO nanopowder with abundant oxygen vacancies. Journal of Materials Research 38, 1211–1223 (2023). https://doi.org/10.1557/s43578-022-00877-8

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