A highly sensitivity and selectivity Pt-SnO2 nanoparticles for sensing applications at extremely low level hydrogen gas detection

By Xi-tao Yin, Wen-Dong Zhou, Jing Li, Qi Wang, Fa-yu Wu, Dong Wang, Hamid Garmestani, Xiang Wang, Ș. Țălu. Journal of Alloys and Compounds, 2019

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Abstract Undecorated and Pt-decorated SnO 2 nanoparticles (NPs) were prepared using sol-gel and hydrothermal methods. The tin dioxide NPs, as sensing materials, were screen printed on alumina substrates with Pt test electrode to fabricate the gas sensors. The characteristics of these gas sensors in terms of composition, morphology, and sensing property were investigated by means of X-ray diffraction (XRD), scanning electron microscopy (SEM), high resolution transmission electron microscopy (HRTEM), X-ray photoelectron spectroscopy (XPS), and electrochemical workstation, respectively. The results elucidated that the response time of Pt-decorated SnO 2 sensor to 100 ppm H 2 is 29 s at 350 °C, which is almost half of that of pure SnO 2 gas sensor. Meanwhile, the effect of operating temperature and Pt decorating on the sensing properties and the ‘n’ value is studied. Comparing with many fabricated H 2 gas sensors, our as-prepared sensor exhibits not only a high response time but also detects H 2 gas down to 0.08 ppm. To the author's best knowledge, the detection limit of 0.08 ppm is the best reported detection limit for the gas sensors based on tin oxide NPs so far. Moreover, there is a significant enhancement in the selectivity of Pt-decorated SnO 2 sensor to the H 2 gas against other investigated gases such as carbon monoxide (CO), methane (CH 4 ), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ). Overall, the obtained results clearly demonstrate that the Pt-decorated SnO 2 is an excellent sensing material for the fabrication of gas sensors and the detection of trace concentration of H 2 down to 0.08 ppm. Furthermore, the results of statistical and fractal analysis on 2D microstructures of FESEM images showed a coefficient correlation of about 0.991 for all the samples.

Subfields: Bioengineering, Biomedical Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/25fca567d83ffc7f7a04e29ebcb97f9b02771143