The substrate plays a key role in chemoresistive gas sensors. It acts as mechanical support for the sensing material, hosts the heating element and, also, aids the sensing material in signal transduction. In recent years, a significant improvement in the substrate production process has been achieved, thanks to the advances in micro- and nanofabrication for micro-electro-mechanical system (MEMS) technologies. In addition, the use of innovative materials and smaller low-power consumption silicon microheaters led to the development of high-performance gas sensors. Various heater layouts were investigated to optimize the temperature distribution on the membrane, and a suspended membrane configuration was exploited to avoid heat loss by conduction through the silicon bulk. However, there is a lack of comprehensive studies focused on predictive models for the optimization of the thermal and mechanical properties of a microheater. In this work, three microheater layouts in three membrane sizes were developed using the microfabrication process. The performance of these devices was evaluated to predict their thermal and mechanical behaviors by using both experimental and theoretical approaches. Finally, a statistical method was employed to cross-correlate the thermal predictive model and the mechanical failure analysis, aiming at microheater design optimization for gas-sensing applications.

Recently, several chemical and physical treatments were developed to improve different properties of wood. Such treatments are applicable to many types of cellulose-based materials. Densification leads the group in terms of mechanical results and comprises a chemical treatment followed by a thermo-compression stage. First, chemicals selectively etch the matrix of lignin and hemicellulose. Then, thermo-compression increases the packing density of cellulose microfibrils boosting mechanical performance. In this paper, in comparison with the state-of-the-art for wood treatments we introduce an additional nano-reinforcemeent on densified giant reed to further improve the mechanical performance. The modified nanocomposite materials are stiffer, stronger, tougher and show higher fire resistance. After the addition of nanoparticles, no relevant structural modification is induced as they are located in the gaps between cellulose microfibrils. Their peculiar positioning could increase the interfacial adhesion energy and improve the stress transfer between cellulose microfibrils. The presented process stands as a viable solution to introduce nanoparticles as new functionalities into cellulose-based natural materials.

Solid-state chemiresistive gas sensors have attracted a lot of researchers’ attention during the last half-century thanks to their ability to detect different gases with high sensitivity, low power consumption, low cost, and high portability. Among the most promising sensitive materials, carbon nanotubes (CNTs) have attracted a lot of interest due to their large active surface area (in the range of 50–1400 m²/g, depending on their composition) and the fact that they can operate at room temperature. In this study, single-walled carbon nanotube (SWCNT)-based sensing films were prepared and deposited by spray deposition for the fabrication of gas sensors. For the deposition, various SWCNTs were prepared in deionized water with the addition of specific surfactants, i.e., carboxymethyl cellulose (CMC) and sodium dodecyl sulfate (SDS), which act as dispersing agents to create a suitable ink for deposition. This study aims to elucidate the possible differences in the sensing performance of the fabricated devices due to the use of the two different surfactants. To achieve this goal, all the devices were tested versus ethanol (C₂H₅OH), carbon monoxide (CO), nitrogen dioxide (NO₂), and ammonia (NH₃). The produced devices demonstrated high selectivity towards NH₃ and NO₂. The different sensors, prepared with different deposition thicknesses (from 0.51 nm to 18.41 nm), were tested in dry and wet conditions (40% humidity), highlighting an enhanced response as a function of relative humidity. In addition, sensor performance was evaluated at different working temperatures, showing the best performance when heated up to 150 °C. The best sensing conditions we found were against NO₂, sensors with 10 layers of deposition and an operating temperature of 150 °C; in this condition, sensors showed high responses compared those found in the literature (62.5%—SDS-based and 78.6%—CMC-based). Finally, cross-sensitivity measurements showed how the produced sensors are good candidates for the practical and selective detection of NO₂, even in the presence of the most important interfering gases identified, i.e., NH₃.

Hybrid nanomaterials fabricated by the heterogeneous integration of 1D (carbon nanotubes) and 2D (graphene oxide) nanomaterials showed synergy in electrical and mechanical properties. Here, we reported the infiltration of carboxylic functionalized single-walled carbon nanotubes (C-SWNT) into free-standing graphene oxide (GO) paper for better electrical and mechanical properties than native GO. The stacking arrangement of GO sheets and its alteration in the presence of C-SWNT were comprehensively explored through scanning electron microscopy, X-ray photoelectron spectroscopy (XPS) and X-ray diffraction. The C-SWNTs bridges between different GO sheets produce a pathway for the flow of electrical charges and provide a tougher hybrid system. The nanoscopic surface potential map reveals a higher work function of the individual functionalised SWNTs than surrounded GO sheets showing efficient charge exchange. We observed the enhanced conductivity up to 50 times and capacitance up to 3.5 times of the hybrid structure than the GO-paper. The laminate of polystyrene composites provided higher elastic modulus and mechanical strength when hybrid paper is used, thus paving the way for the exploitation of hybrid filler formulation in designing polymer composites.

Over the last few years, employment of the standard silicon microfabrication techniques for the gas sensor technology has allowed for the development of ever-small, low-cost, and low-power consumption devices. Specifically, the development of silicon microheaters (MHs) has become well established to produce MOS gas sensors. Therefore, the development of predictive models that help to define a priori the optimal design and layout of the device have become crucial, in order to achieve both low power consumption and high mechanical stability. In this research dataset, we present the experimental data collected to develop a specific and useful predictive thermal-mechanical model for high performing silicon MHs. To this aim, three MH layouts over three different membrane sizes were developed by using the standard silicon microfabrication process. Thermal and mechanical performances of the produced devices were experimentally evaluated, by using probe stations and mechanical failure analysis, respectively. The measured thermal curves were used to develop the predictive thermal model towards low power consumption. Moreover, a statistical analysis was finally introduced to cross-correlate the mechanical failure results and the thermal predictive model, aiming at MH design optimization for gas sensing applications. All the data collected in this investigation are shown.