High quality nanocrystalline NiO nanoplates were synthesized using surfactant and template free hydrothermal route. The gas sensing properties of NiO nanoplates were investigated. The nanoplates morphology of NiO with average thickness ~20 nm and diameter ~100 nm has been confirmed by FE-SEM and TEM. Crystalline quality of NiO has been studied using HRTEM and SAED techniques. Structural properties and elemental compositions have been analysed by XRD and energy dispersive spectrometer (EDS) respectively. The detailed investigation of structural parameters has been carried out. The optical properties of NiO were analyzed from UV-Visible and photoluminescence spectra. NiO nanoplates have good selectivity towards hydrogen (H2) gas. The lowest H2 response of 3% was observed at 2 ppm, whereas 90% response was noted for 100 ppm at optimized temperature of 200 °C with response time 180 s. The H2 responses as functions of different operating temperature as well as gas concentrations have been studied along with sensor stability. The hydrogen sensing mechanism was also elucidated.
The application of metal-organic frameworks (MOFs) as a sensing layer has been attracting great interest over the last decade, due to their uniform properties in terms of high porosity and tunability, which provides a large surface area and/or centers for trapping/binding a targeted analyte. Here we report the fabrication of a highly sensitive humidity sensor that is based on composite thin films of HKUST-1 MOF and carbon nanotubes (CNT). The composite sensing films were fabricated by spin coating technique on a quartz-crystal microbalance (QCM) and a comparison of their shift in resonance frequencies to adsorbed water vapor (5 to 75% relative humidity) is presented. Through optimization of the CNT and HKUST-1 composition, we could demonstrate a 230% increase in sensitivity compared to plain HKUST-1 film. The optimized CNT-HKUST-1 composite thin films are stable, reliable, and have an average sensitivity of about 2.5×10−5 (Δf/f) per percent of relative humidity, which is up to ten times better than previously reported QCM-based humidity sensors. The approach presented here is facile and paves a promising path towards enhancing the sensitivity of MOF-based sensors.
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