Nanosensor Based on Thermal Gradient and Machine Learning for the Detection of Methanol Adulteration in Alcoholic Beverages and Methanol Poisoning (original) (raw)

Sensors

Methanol, naturally present in small quantities in the distillation of alcoholic beverages, can lead to serious health problems. When it exceeds a certain concentration, it causes blindness, organ failure, and even death if not recognized in time. Analytical techniques such as chromatography are used to detect dangerous concentrations of methanol, which are very accurate but also expensive, cumbersome, and time-consuming. Therefore, a gas sensor that is inexpensive and portable and capable of distinguishing methanol from ethanol would be very useful. Here, we present a resistive gas sensor, based on tin oxide nanowires, that works in a thermal gradient. By combining responses at various temperatures and using machine learning algorithms (PCA, SVM, LDA), the device can distinguish methanol from ethanol in a wide range of concentrations (1–100 ppm) in both dry air and under different humidity conditions (25–75% RH). The proposed sensor, which is small and inexpensive, demonstrates the...

Selective discrimination of hazardous gases using one single metal oxide resistive sensor

<<< Final published version for free until October 27th: https://authors.elsevier.com/a/1XhJP3IQMPAqsP >>> Monitoring of hazardous gases is nowadays very important, since the urbanized environment is more subject to this kind of pollutants. Therefore, a capillary network of small gas sensors capable to check the quality of the environment is necessary. Metal oxide gas nanosensors are small economic devices that can be easily integrated in any context, however they unfortunately lack of selectivity. We present an approach using hydrothermally grown nickel oxide nanowires working at different temperatures and creating a virtual sensors array, thus exploiting the thermal fingerprints (sensor response as a function of temperature) of the gases. Using only one nanostructured material (nickel oxide) and different machine learning techniques, the system can easily discriminate any of 7 harmful gases (C 2 H 5 OH, H 2 , CO, LPG, CO 2 , NH 3 and H 2 S, all of them reducing gases) with an accuracy of 100%. Furthermore, the nanosensor also evaluates the gas concentration with an average error lower than 15%. Our results show that, exploiting thermal fingerprints from a temperature gradient, single metal oxide resistive nanosensors can efficiently discriminate specific hazardous gases.

Embedded Transdermal Alcohol Detection via a Finger Using SnO2 Gas Sensors

Sensors, 2021

In this paper, we report the fabrication and characterization of a portable transdermal alcohol sensing device via a human finger, using tin dioxide (SnO2) chemoresistive gas sensors. Compared to conventional detectors, this non-invasive technique allowed us the continuous monitoring of alcohol with low cost and simple fabrication process. The sensing layers used in this work were fabricated by using the reactive radio frequency (RF) magnetron sputtering technique. Their structure and morphology were investigated by means of X-ray spectroscopy (XRD) and scanning electron microscopy (SEM), respectively. The results indicated that the annealing time has an important impact on the sensor sensitivity. Before performing the transdermal measurements, the sensors were exposed to a wide range of ethanol concentrations and the results displayed good responses with high sensitivity, stability, and a rapid detection time. Moreover, against high relative humidity (50% and 70%), the sensors rema...

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