A novel approach to fabricating a ternary rGO/ZnO/Pt system for high-performance hydrogen sensor at low operating temperatures
Source abstract
Abstract
Abstract A novel method for the synthesis of a ternary platinum loaded reduced graphene oxide (rGO)/ zinc oxide (ZnO) hybrid nanocomposite via a pulsed laser ablation in liquid (PLAL) and direct current (DC) sputtering for a hydrogen sensing application is reported here. The said composite was fabricated to obtain small ZnO nanoparticles with interfacial electric contact without using chemical reagents. Firstly, ZnO nanoparticles were fabricated by the decomposition of zinc peroxide (ZnO2) quantum dots, synthesized by laser ablation of microstructured Zn powder in 3%H2O2, whereas GO was prepared by the modified Hummer method. Secondly, an rGO/ZnO nanocomposite was prepared via PLAL of ZnO and graphene oxide (GO) in deionized water. Finally, DC sputtering was used to decorate the surface of the rGO/ZnO hybrid with a Pt thin film to obtain a ternary rGO/ZnO/Pt hybrid nanocomposite. Maximum sensing performance was achieved by tuning the thickness of the deposited Pt layer. According to our study, the Pt-loaded rGO/ZnO gas sensor, with a thickness of 2 nm, showed an excellent response and selectivity towards a low concentration of hydrogen, giving a high response of about 99% (−400 ppm), which was 10 and 5 times higher than those of the pure ZnO, and the rGO/ZnO nanocomposite, respectively. This significantly improved response was mainly attributed to the high surface area of the rGO, the fast spill-over effect of the uniformly coated Pt nanoparticles, and the formation of a p-n junction between rGO and ZnO nanoparticles. This study indicates that the obtained rGO/ZnO/Pt hybrid nanocomposite is a promising candidate for constructing high-performance H2 gas sensors.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Gas Sensing Nanomaterials and Sensors · Analytical Chemistry and Sensors · Air Quality Monitoring and Forecasting
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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