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Towards Selective and Sensitive Detection of Carbon Monoxide with CuO/ZnO Heterojunction NanocompositePrepared by an Organometallic Approach
- Source :
- Sensors & Transducers Journal, Sensors & Transducers Journal, 2022, 259 (5), pp.99-108
- Publication Year :
- 2022
- Publisher :
- HAL CCSD, 2022.
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Abstract
- International audience; Nanometer size p-n heterojunction has been created from CuO and ZnO anisotropic nanoparticles prepared by a one-pot organometallic approach. The method is based on the hydrolysis or oxidation of an adequate metal-organic precursors in pure octylamine. The CuO and ZnO nanostructures were dispersed in ethanol and then, mixed at different mass ratios, i.e. CuO(75%)/ZnO(25%), CuO(50%)/ZnO(50%) and CuO(25%)/ZnO(75%). Finally, the CuO and ZnO suspensions and their mixtures were deposited on miniaturized gas sensors substrates by an ink-jet printing method and heated up gradually to 550 oC in ambient air. Then, the as-prepared sensors have been exposed to CO (100 ppm), C3H8 (100 ppm) and NH3 (5 ppm) at different working temperatures (from 75 oC to 400 oC) and under 50 % of relative humidity (RH). Among all prepared sensors the one based on the mixture of CuO (75 %) and ZnO (25 %) presents a very sensitive and selective response to CO. Indeed, at the operating temperature of 165 oC, a high sensitivity towards CO was obtained (SCO=624 %). In these conditions, the sensor exhibited low sensitivity to other tested gases (KCO/C3H8= 14.5 and KCO/NH3= 26) but its response time was quite long (t90=2.3 min) and the recovery was very sluggish (t10>20 min). Therefore, it was better to increase the working temperature up to 300 oC. Although the sensitivity and selectivity towards CO worsened (SCO=177%, KCO/C3H8= 4.7 and KCO/NH3= 9.8) the response/recovery time decreased to 50 s/4.5 min. The gas sensing performances of the CuO(75%)/ZnO(25%) composite was attributed to both high surface to volume ratio of the prepared nanostructures and the p-n heterojunction established between the CuO and ZnO nanoparticles.
Details
- Language :
- English
- ISSN :
- 17265479
- Database :
- OpenAIRE
- Journal :
- Sensors & Transducers Journal, Sensors & Transducers Journal, 2022, 259 (5), pp.99-108
- Accession number :
- edsair.od......4074..10c8f07b3927f8631b1f99967b725b2a