Comparison of Fast Response and Recovery Pd Nanoparticles and Ni Thin Film Hydrogen Gas Sensors Based on Metal-Oxide-Semiconductor Structure

NANO ◽  
2017 ◽  
Vol 12 (08) ◽  
pp. 1750096 ◽  
Author(s):  
G. Behzadi Pour ◽  
L. Fekri Aval

In this study, two hydrogen sensors with Pd/SiO2/Si and Ni/SiO2/Si structures have been fabricated. Palladium nanoparticles are synthesized and then deposited on the oxide surface using spin coating. Capacitance–voltage curves for the Pd/SiO2/Si sensor at room temperature and for the Ni/SiO2/Si sensor at 140[Formula: see text]C in pure nitrogen and 1% H2–N2 mixture are described. The time required for reaching 90% of the steady-state signal magnitude ([Formula: see text]) for Pd/SiO2/Si capacitor was 1.4[Formula: see text]s and for Ni/SiO2/Si capacitor was 90 s. The time interval for recovery from 90% to 10% of steady-state signal magnitude ([Formula: see text] for Pd/SiO2/Si capacitor was 14[Formula: see text]s and for Ni/SiO2/Si capacitor was 40[Formula: see text]min. For the Pd/SiO2/Si capacitor, the response is 88% and for Ni/SiO2/Si capacitor the response is 29%. Comparison of Pd nanoparticles capacitive- and resistance-based sensors shows that the metal-oxide-semiconductor capacitive is faster and more sensitive than the resistance-based hydrogen gas sensors.

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 647
Author(s):  
Tobias Baur ◽  
Johannes Amann ◽  
Caroline Schultealbert ◽  
Andreas Schütze

More and more metal oxide semiconductor (MOS) gas sensors with digital interfaces are entering the market for indoor air quality (IAQ) monitoring. These sensors are intended to measure volatile organic compounds (VOCs) in indoor air, an important air quality factor. However, their standard operating mode often does not make full use of their true capabilities. More sophisticated operation modes, extensive calibration and advanced data evaluation can significantly improve VOC measurements and, furthermore, achieve selective measurements of single gases or at least types of VOCs. This study provides an overview of the potential and limits of MOS gas sensors for IAQ monitoring using temperature cycled operation (TCO), calibration with randomized exposure and data-based models trained with advanced machine learning. After lab calibration, a commercial digital gas sensor with four different gas-sensitive layers was tested in the field over several weeks. In addition to monitoring normal ambient air, release tests were performed with compounds that were included in the lab calibration, but also with additional VOCs. The tests were accompanied by different analytical systems (GC-MS with Tenax sampling, mobile GC-PID and GC-RCP). The results show quantitative agreement between analytical systems and the MOS gas sensor system. The study shows that MOS sensors are highly suitable for determining the overall VOC concentrations with high temporal resolution and, with some restrictions, also for selective measurements of individual components.


Gas Sensors ◽  
2020 ◽  
Author(s):  
Nazar Abbas Shah ◽  
Majeed Gul ◽  
Murrawat Abbas ◽  
Muhammad Amin

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2646 ◽  
Author(s):  
Henike Guilherme Jordan Voss ◽  
José Jair Alves Mendes Júnior ◽  
Murilo Eduardo Farinelli ◽  
Sergio Luiz Stevan

Due to the emergence of new microbreweries in the Brazilian market, there is a need to construct equipment to quickly and accurately identify the alcohol content in beverages, together with a reduced marketing cost. Towards this purpose, the electronic noses prove to be the most suitable equipment for this situation. In this work, a prototype was developed to detect the concentration of ethanol in a high spectrum of beers presents in the market. It was used cheap and easy-to-acquire 13 gas sensors made with a metal oxide semiconductor (MOS). Samples with 15 predetermined alcohol contents were used for the training and construction of the models. For validation, seven different commercial beverages were used. The correlation (R2) of 0.888 for the MLR (RMSE = 0.45) and the error of 5.47% for the ELM (RMSE = 0.33) demonstrate that the equipment can be an effective tool for detecting the levels of alcohol contained in beverages.


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