HighlightsWhat are the main findings?The problem of dichloromethane “poisoned” MOS materials was well solved.Gas sensing mechanism of dichloromethane on the MOS material was elucidate.What is the implication of the main finding?The best performance of significant response and excellent recoverability by the MEMS sensor to dichloromethane is attributed to a synergetic effect from Mo and Ni co-doping into SnO2.Kinetically, the transportation of dichloromethane molecules onto the surface determines the response process. Thermodynamically, the output steady electronic signal of the MEMS sensor follows the equations newly derived by statistical mechanics.The challenging problem of chlorine “poisoning” SnO2for poorly recoverable detection of dichloromethane has been solved in this work. The materials synthesized by Ni or/and Mo doping SnO2were spread onto the micro-hotplates (<1 mm3) to fabricate the MEMS sensors with a low power consumption (<45 mW). The sensor based on Mo·Ni co-doped SnO2is evidenced to have the best sensing performance of significant response and recoverability to dichloromethane between 0.07 and 100 ppm at the optimized temperature of 310 °C, in comparison with other sensors in this work and the literature. It can be attributed to a synergetic effect of Mo·Ni co-doping into SnO2as being supported by characterization of geometrical and electronic structures. The sensing mechanism of dichloromethane on the material is investigated. In situ infrared spectroscopy (IR) peaks identify that the corresponding adsorbed species are too strong to desorb, although it has demonstrated a good recoverability of the material. A probable reason is the formation rates of the strongly adsorbed species are much slower than those of the weakly adsorbed species, which are difficult to form significant IR peaks but easy to desorb, thus enabling the material to recover. Theoretical analysis suggests that the response process is kinetically determined by molecular transport onto the surface due to the free convection from the concentration gradient during the redox reaction, and the output steady voltage thermodynamically follows the equation only formally identical to the Langmuir–Freundlich equation for physisorption but is newly derived from statistical mechanics.
We report the fabrication of screw-like SnO 2 nanostructure and its application as photoanode for photoelectrochemical water splitting . The structure was formed by growing thread-like SnO 2 nanosheets onto rod-like single-crystalline SnO 2 nanowires . Such a structure offers an efficient light absorption, high speed electron transport and a large surface-to-volume ratio. The light absorption efficiency of the screw-like SnO 2 nanostructures can be increased by up to 33% than that of the pristine SnO 2 nanowires. After decorated with CdS quantum dots , the photocurrent density can reach 9.9 mA cm −2 at 0 V ( versus saturated calomel electrode) which corresponding to a hydrogen generation of 159.6 μmol (h cm 2 ) −1 and the faradic efficiency is around 86%. The result demonstrated that the water-splitting efficiency of photoelectrochemical cell has been significantly improved by using such a screw-like structure. Our work provides an efficient solution to improve the water-splitting performance and it can also be a model structure for similar electrode materials.
Dynamic working temperature modulation has received considerable attention as a way to enable metal oxide-based gas sensors to recognize the detected gases. Previous reports mainly focused on heating-voltage waveform manipulation and algorithm improvement, not involving the insight of the temperature modulation sensing behavior correlated with fine nanostructures of metal oxide. Here, three types of SnO2 nanoparticles with different percentages of high-energy {221} and low-energy {110} crystal facets were synthesized and assembled as gas sensors. Under a working temperature modulation by applying a square wave pulse heating voltage, their dynamic response behaviors toward volatile organic compounds (VOCs) including alcohols, aldehydes, ketones, amines, and aromatic compounds were systematically explored. The results indicated that they exhibited different characteristic response curves toward different VOCs, presenting the crystal facet-dependent temperature modulation sensing behaviors. This effect was analyzed further and explored in conjunction with the characteristic response curves. Based on their different characteristic response curves that occurred on the three types of SnO2 nanoparticles, the detected gases, and even some congeners, were well discriminated along with a simple PCA recognition algorithm. Additionally, their quantitative analysis was also achieved.
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