Tunable formation of nanostructured SiC/SiOC core-shell for selective detection of SO2

Gaiardo, Andrea; Fabbri, Barbara; Giberti, A; Valt, Matteo; Gherardi, S.; Guidi, V.; Malagù, C.; Bellutti, P.; Pepponi, G.; Casotti, Davide; Cruciani, Giuseppe; Zonta, Giulia; Landini, Nicolò; Barozzi, M.; Morandi, Sara; Vanzetti, L.; Canteri, R.; Ciana, Michele Della; Migliori, Andrea; Demenev, Evgeny

doi:10.1016/j.snb.2019.127485

Cited by 29 publications

(28 citation statements)

References 95 publications

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“…The alumina substrates were equipped with interdigitated gold electrodes on the top-side and platinum heaters on the back-side of the substrates [ 24 ]. The thickness of the deposition was about 20–30 µm [ 13 ].…”

Section: Methodsmentioning

confidence: 99%

“…In particular, specifically calibrated arrays of MOX gas sensors equipped with a dedicated algorithm have proven to be suitable for different applications [ 11 ]. On the other hand, great effort has been devoted to the study and development of advanced nanostructured sensing materials, by considering both MOX and other types of semiconductors [ 7 , 12 , 13 , 14 , 15 ]. The most used techniques were based on the addition of catalysts to the MOX nanostructure surface, on the synthesis of different MOX morphologies and on the preparation of MOX solid solutions [ 6 , 7 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

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Nanostructured SmFeO3 Gas Sensors: Investigation of the Gas Sensing Performance Reproducibility for Colorectal Cancer Screening

Gaiardo

Zonta

Gherardi

et al. 2020

Sensors

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Among the various chemoresistive gas sensing properties studied so far, the sensing response reproducibility, i.e., the capability to reproduce a device with the same sensing performance, has been poorly investigated. However, the reproducibility of the gas sensing performance is of fundamental importance for the employment of these devices in on-field applications, and to demonstrate the reliability of the process development. This sensor property became crucial for the preparation of medical diagnostic tools, in which the use of specific chemoresistive gas sensors along with a dedicated algorithm can be used for screening diseases. In this work, the reproducibility of SmFeO3 perovskite-based gas sensors has been investigated. A set of four SmFeO3 devices, obtained from the same screen-printing deposition, have been tested in laboratory with both controlled concentrations of CO and biological fecal samples. The fecal samples tested were employed in the clinical validation protocol of a prototype for non-invasive colorectal cancer prescreening. Sensors showed a high reproducibility degree, with an error lower than 2% of the response value for the test with CO and lower than 6% for fecal samples. Finally, the reproducibility of the SmFeO3 sensor response and recovery times for fecal samples was also evaluated.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nanostructured SmFeO3 Gas Sensors: Investigation of the Gas Sensing Performance Reproducibility for Colorectal Cancer Screening

Gaiardo

Zonta

Gherardi

et al. 2020

Sensors

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“…Indeed, both SiC nanoparticles and GO flakes were intercalated into the pores of giant reed, which were opened through chemical treatment and then closed by thermo-compression (Figure 1, Figure 2a). It can be interpreted in terms of better interfacial adhesion or increased in the chemical cross-linking at the interface driven by the additional hydrogen bonds available from the GO structure [48,49] and the nonstoichiometric oxides shell (Figure 2i) on SiC nanostructures [50,51]. Not to mention that the small amount of Ca impurities, which was found in all the samples (see Figure S1), was reported to have a beneficial effect on the chemical cross-linking between GO and cellulose [52], thus effectively enhancing the stiffness and the strength between GO layers [53].…”

Section: Resultsmentioning

confidence: 99%

Strengthening of Wood-like Materials via Densification and Nanoparticle Intercalation

et al. 2020

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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.

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“…There is a significant demand for small, low-cost and high-performance gas sensors in several sectors, including chemical process control, precision agriculture, environmental monitoring, and medical applications [1][2][3][4][5]. Among the various new classes of smart gas detectors, one of the most investigated and used are the chemoresistive gas sensors, which show high sensitivity, allowing to detect low concentrations of gases (ppm-ppb range) with high accuracy [6][7][8][9]. These devices are composed of an active sensing material, typically nanostructured metal oxide semiconductors (MOS), and a heated substrate [6,[10][11][12].…”

Section: Discussionmentioning

confidence: 99%

Dataset of the Optimization of a Low Power Chemoresistive Gas Sensor: Predictive Thermal Modelling and Mechanical Failure Analysis

Gaiardo

Novel

Scattolo

et al. 2021

Data

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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.

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Tunable formation of nanostructured SiC/SiOC core-shell for selective detection of SO2

Cited by 29 publications

References 95 publications

Nanostructured SmFeO3 Gas Sensors: Investigation of the Gas Sensing Performance Reproducibility for Colorectal Cancer Screening

Nanostructured SmFeO3 Gas Sensors: Investigation of the Gas Sensing Performance Reproducibility for Colorectal Cancer Screening

Strengthening of Wood-like Materials via Densification and Nanoparticle Intercalation

Dataset of the Optimization of a Low Power Chemoresistive Gas Sensor: Predictive Thermal Modelling and Mechanical Failure Analysis

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