Constructing hierarchical SnO2 nanofiber/nanosheets for efficient formaldehyde detection

Abstract SnO2 nanofiber/nanosheets with hierarchical nanostructures were successfully synthesized via a facile hydrothermal method by using hollow SnO2 nanofibers as the backbone. The microstructure, morphology, chemical composition, oxidation states and surface areas of SnO2 nanofibers, SnO2 nanofiber/nanosheets and SnO2 nanosheets were comparatively studied by X-ray diffraction (XRD), Field emission scanning electron microscopy (FE-SEM), Transmission electron microscope (TEM), X-ray photoelectron spectroscopy (XPS), and Brunauer-Emmett-Teller (BET). The characterization results indicated that the hierarchical SnO2 nanofiber/nanosheets were constructed by nanosheets arrays uniform growth on the surface of nanofibers. Sensing performances of SnO2-based nanomaterials were investigated utilizing formaldehyde (HCHO) as a target gas. Compared to SnO2 nanofibers, nanosheets and the physical mixture of nanofibers and nanosheets, the gas sensor based on SnO2 nanofiber/nanosheets exhibited better response, more excellent selectivity, transient response and trace detection ability to HCHO gas. The response (Ra/Rg) of the gas sensor is 57 toward 100 ppm HCHO at 120 °C, which is about 300% and 200% higher than that of pure SnO2 nanofibers sensors and SnO2 nanosheets sensors, respectively. Furthermore, the sensor has an excellent response/recovery performance with 4.7 s and 11.6 s for detecting 100 ppm HCHO. Both the growth process and the gas sensing mechanism of SnO2 hierarchical nanostructures were discussed. Successful preparation of SnO2 nanofiber/nanosheets is attributed to uniform decoration of seeds on the nanofibers and suitable growth conditions of nanosheets. Enhanced sensing performance mainly result from the synergistic effect of nanofibers and nanosheets, hierarchical structures and larger specific surface areas. The synthetic strategy can also be applied in preparing hierarchical materials of different constituent materials.