Electronic Nose for Improved Environmental Methane Monitoring.

Reducing emissions of the key greenhouse gas methane (CH4) is increasingly highlighted as being important to mitigate climate change. Effective emission reductions require cost-effective ways to measure CH4 to detect sources and verify that mitigation efforts work. We present here a novel approach to measure methane at atmospheric concentrations by means of a low-cost electronic nose strategy where the readings of a few sensors are combined, leading to errors down to 33 ppb and coefficients of determination, R2, up to 0.91 for in situ measurements. Data from methane, temperature, humidity, and atmospheric pressure sensors were used in customized machine learning models to account for environmental cross-effects and quantify methane in the ppm-ppb range both in indoor and outdoor conditions. The electronic nose strategy was confirmed to be versatile with improved accuracy when more reference data were supplied to the quantification model. Our results pave the way toward the use of networks of low-cost sensor systems for the monitoring of greenhouse gases.

A Virtual Electronic Nose for the Efficient Classification and Quantification of Volatile Organic Compounds.

Although many chemical gas sensors report high sensitivity towards volatile organic compounds (VOCs), finding selective gas sensing technologies that can classify different VOCs is an ongoing and highly important challenge. By exploiting the synergy between virtual electronic noses and machine learning techniques, we demonstrate the possibility of efficiently discriminating, classifying, and quantifying short-chain oxygenated VOCs in the parts-per-billion concentration range. Several experimental results show a reproducible correlation between the predicted and measured values. A 10-fold cross-validated quadratic support vector machine classifier reports a validation accuracy of 91% for the different gases and concentrations studied. Additionally, a 10-fold cross-validated partial least square regression quantifier can predict their concentrations with coefficients of determination, R2, up to 0.99. Our methodology and analysis provide an alternative approach to overcoming the issue of gas sensors' selectivity, and have the potential to be applied across various areas of science and engineering where it is important to measure gases with high accuracy.

Assessing the consequences of prolonged usage of disposable face masks.

Due to the SARS-CoV-2 outbreak, wearing a disposable face mask has become a worldwide daily routine, not only for medical operators or specialized personnel, but also for common people. Notwithstanding the undeniable positive effect in reducing the risk of virus transmission, it is important to understand if a prolonged usage of the same face mask can have effectiveness on filtering capability and potential health consequences. To this aim, we present three investigations. A survey, carried out in central Italy, offers an overview of the distorted public awareness of face mask usage. A functional study shows how prolonged wearing leads to substantial drops in humid air filtration efficiency. Finally, a morphological analysis reports the proliferation of fungal or bacteria colonies inside an improperly used mask. Our study highlights therefore that wearing a face mask is really beneficial only if it is used correctly.

Fabrication, Characterization and Performance of Low Power Gas Sensors Based on (GaxIn1-x)2O3 Nanowires.

Active research in nanostructured materials aims to explore new paths for improving electronic device characteristics. In the field of gas sensors, those based on metal oxide single nanowires exhibit excellent sensitivity and can operate at extremely low power consumption, making them a highly promising candidate for a novel generation of portable devices. The mix of two different metal oxides on the same nanowire can further broaden the response of this kind of gas sensor, thus widening the range of detectable gases, without compromising the properties related to the active region miniaturization. In this paper, a first study on the synthesis, characterization and gas sensing performance of (GaxIn1-x)2O3 nanowires (NWs) is reported. Carbothermal metal-assisted chemical vapor deposition was carried out with different mixtures of Ga2O3, In2O3 and graphite powders. Structural characterization of the NWs revealed that they have a crystalline structure close to that of In2O3 nanowires, with a small amount of Ga incorporation, which highly depends on the mass ratio between the two precursors. Dedicated gas nanosensors based on single NWs were fabricated and tested for both ethanol and nitrogen dioxide, demonstrating an improved performance compared to similar devices based on pure In2O3 or Ga2O3 NWs.

Site-Specific Growth and in Situ Integration of Different Nanowire Material Networks on a Single Chip: Toward a Nanowire-Based Electronic Nose for Gas Detection.

A new method for the site-selective synthesis of nanowires has been developed to enable material growth with defined morphology and, at the same time, different composition on the same chip surface. The chemical vapor deposition approach for the growth of these nanowire-based resistive devices using micromembranes can be easily modified and represents a simple, adjustable fabrication process for the direct integration of nanowire meshes in multifunctional devices. This proof-of-concept study includes the deposition of SnO2, WO3, and Ge nanowires on the same chip. The individual resistors exhibit adequate gas sensing responses toward changing gas concentrations of CO, NO2, and humidity diluted in synthetic air. The data have been processed by principal component analysis with cluster responses that can be easily separated, and thus, the devices described herein are in principle suitable for environmental monitoring.