Layered Double Hydroxide-Based Gas Sensors for VOC Detection at Room Temperature.

Miniaturized low-cost sensors for volatile organic compounds (VOCs) have the potentiality to become a fundamental tool for indoor and outdoor air quality monitoring, to significantly improve everyday life. Layered double hydroxides (LDHs) belong to the class of anionic clays and are largely employed for NO x detection, while few results are reported on VOCs. In this work, a novel LDH coprecipitation method is proposed. For the first time, a study comparing four LDHs (ZnAl-Cl, ZnFe-Cl, ZnAl-NO3, and MgAl-NO3) is carried out to investigate the sensing performances. As explored through several microscopy and spectroscopy analyses, LDHs show a morphology characterized by a large surface area and a three-dimensional hierarchical flowerlike architecture with micro- and nanopores that induce a fast diffusion and highly effective surface interaction of the target gases. The fabricated sensors, operating at room temperature, are able to reversibly and selectively detect acetone, ethanol, ammonia, and chlorine vapors, reaching significant sensing response values up to 6% at 21 °C. The results demonstrate that by changing the LDHs' composition, it is possible to modulate the sensitivity and selectivity of the sensor, helping the discrimination of different analytes, and the consequent integration on a sensor array paves the way for electronic nose development.

Predicting Composite Component Behavior Using Element Level Crashworthiness Tests, Finite Element Analysis and Automated Parametric Identification.

Fibre reinforced plastics have tailorable and superior mechanical characteristics compared to metals and can be used to construct relevant components such as primary crash structures for automobiles. However, the absence of standardized methodologies to predict component level damage has led to their underutilization as compared to their metallic counterparts, which are used extensively to manufacture primary crash structures. This paper presents a methodology that uses crashworthiness results from in-plane impact tests, conducted on carbon-fibre reinforced epoxy flat plates, to tune the related material card in Radioss using two different parametric identification techniques: global and adaptive response search methods. The resulting virtual material model was then successfully validated by comparing the crushing behavior with results obtained from experiments that were conducted by impacting a Formula SAE (Society of Automotive Engineers) crash box. Use of automated identification techniques significantly reduces the development time of composite crash structures, whilst the predictive capability reduces the need for component level tests, thereby making the development process more efficient, automated and economical, thereby reducing the cost of development using composite materials. This in turn promotes the development of vehicles that meet safety standards with lower mass and noxious gas emissions.