Limited selectivity of amperometric gas sensors operating in multicomponent gas mixtures and methods of selectivity improvement

• Autorzy: Dmitrzak Marta , Jasinski Piotr , Jasinski Grzegorz

Identyfikatory

DOI

10.24425/bpasts.2020.134648

• Języki publikacji: EN

Abstrakty

EN

In recent years, smog and poor air quality have become a growing environmental problem. There is a need to continuously monitor the quality of the air. The lack of selectivity is one of the most important problems limiting the use of gas sensors for this purpose. In this study, the selectivity of six amperometric gas sensors is investigated. First, the sensors were calibrated in order to find a correlation between the concentration level and sensor output. Afterwards, the responses of each sensor to single or multicomponent gas mixtures with concentrations from 50 ppb to 1 ppm were measured. The sensors were studied under controlled conditions, a constant gas flow rate of 100 mL/min and 50 % relative humidity. Single Gas Sensor Response Interpretation, Multiple Linear Regression, and Artificial Neural Network algorithms were used to predict the concentrations of SO2 and NO2. The main goal was to study different interactions between sensors and gases in multicomponent gas mixtures and show that it is insufficient to calibrate sensors in only a single gas.

Słowa kluczowe

EN

gas sensor; amperometric sensor; cross-sensitivity; multiple linear regression; artificial neural networks

PL

czujnik gazu; czujnik amperometryczny; nadwrażliwość krzyżowa; regresja liniowa wielokrotna; sztuczne sieci neuronowe

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2020
• Tom: Vol. 68, nr 6
• Strony: 1275--1282
• Opis fizyczny: Bibliogr. 22 poz., rys., tab.

Twórcy

autor

Dmitrzak Marta

• Gdansk University of Technology, ul. Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland
• PM Ecology sp. z o.o., ul. Kielnieńska 136, 80-299 Gdańsk, Poland

autor

Jasinski Piotr

• Gdansk University of Technology, ul. Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland

autor

Jasinski Grzegorz

• Gdansk University of Technology, ul. Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland

Bibliografia

• [1] Air quality in Europe – 2019 report, European Environment Agency, No 10/2019, ISSN 1977‒8449, Denmark, 2019.
• [2] N. Barsan, D. Koziej, and U. Weimar, “Metal oxide-based gas sensor research: How to?”, Sens. Actuators B: Chem. 121, 18‒35 (2007).
• [3] A. Dey, “Semiconductor metal oxide gas sensors: A review”, Mater. Sci. Eng. B. 229, 206‒217 (2018).
• [4] Z. Lei, T. Feng-Chun, P. Xiong-Wei, and Y. Xin, “A rapid discreteness correction scheme for reproducibility enhancement among a batch of MOS gas sensors”, Sens. Actuators A: Phys. 205, 170–176 (2014).
• [5] Y. Xu, X. Zhao, Y. Chen, and W. Zhao, “Research on a mixed gas recognition and concentration detection algorithm based on a metal oxide semiconductor olfactory system sensor array”, Sensors 18(10), 3264 (2018).
• [6] J.E. Haugen, and K. Kvaal, “Electronic nose and artificial neural network”, Meat Sci. 49, S273-S286 (1998).
• [7] S. Omatu and M. Yano, „E-nose system by using neural networks”, Neurocomputing 172, 394‒398 (2016).
• [8] M.N. Abbas, G.A. Moustafa, and W. Gopel, “Multicomponent data analysis of some environmentally important gases using semiconductor tin oxide sensors”, Anal. Chim. Acta 431, 181–194 (2001).
• [9] T. Pustelny, M. Procek, E. Maciak, A. Stolarczyk, S. Drewniak, M. Urbańczyk, M. Setkiewicz, K. Gut, and Z. Opilski, “Gas sensor based on nanostructures of semiconductors ZnO and TiO2”, Bull. Pol. Ac.: Tech. 60(4), 853‒859 (2012).
• [10] T. Pustelny et al., “The sensibility of resistance sensor structures with graphene to the action of selected gaseous media”, Bull. Pol. Ac.: Tech. 61(2), 293‒300 (2013).
• [11] C. Melios, V. Panchal, K. Edmonds, A. Lartsev, R. Yakimova, and O. Kazakova, “Detection of ultralow concentration NO2 in complex environment using epitaxial graphene sensors”, ACS Sens. 3(9), 1666‒1674 (2018).
• [12] F. Schedin, A.K. Geim, S.V. Morozov, E.W. Hill, P. Blake, M.I. Katsnelson, and K.S. Novoselov, “Detection of individual gas molecules adsorbed on graphene”, Nat. Mater. 6(9), 652–655 (2007).
• [13] M. Blagojevic, M. Papic, M. Vujicic, and M. Sucurovic, “Artificial neural network model for predicting air pollution. Case study of the Moravia district, Serbia”, Environ. Prot. Eng. 44(1), 129‒139 (2018).
• [14] H. Sundgren, F. Winquist, I. Lukkari, and I. Lundstrom, “Artificial neural networks and gas sensor arrays: quantification of individual components in a gas mixture”, Meas. Sci. Technol. 2, 464‒469 (1991).
• [15] A. Loutfi, S. Coradeschi, G. K. Mani, P. Shankar, and J.B.B. Rayappan, “Electronic noses for food quality: A review”, J. Food Eng. 144, 103‒111 (2015).
• [16] J.S. Do and P.J. Chen, “Amperometric sensor array for NOx, CO, O2 and SO2 detection”, Sens. Actuators B: Chem. 122, 165‒173 (2007).
• [17] S. Osowski, K. Brudzewski, and L. Tran Hoai, “Modified neuro-fuzzy TSK network and its application in electronic nose”, Bull. Pol. Ac.: Tech. 61(3), 675‒680 (2013).
• [18] R. Baron and J. Saffell, “Amperometric gas sensors as a low cost emerging technology platform for air quality monitoring applications: A review”, ACS Sens. 2 (11), 1553‒1566 (2017).
• [19] M.M. Rahman, C. Charoenlarpnopparut, P. Suksompong, P. Toochinda, and A. Taparugssanagorn, “A false alarm reduction method for a gas sensor based electronic nose”, Sensors 17(9). 2089 (2017).
• [20] M. Hossain, J. Saffell, and R. Baron, “Differentiating NO2 and O3 at low cost air quality amperometric gas sensors”, ACS Sens. 1(11), 1291‒1294 (2016).
• [21] G. Jasinski, A. Strzelczyk, and P. Koscinski, “Low cost electrochemical sensor module for measurement of gas concentration”, IOP Conf. Ser.: Mater. Sci. Eng. 104, 012034 (2015).
• [22] G. Jasinski, P. Kalinowski, L. Wozniak, and P. Jasinski, “An electronic nose based on the semiconducting and electrochemical gas sensors”, in 2017 21st European Microelectronics and Packaging Conference (EMPC) & Exhibition, Warsaw, Poland, pp. 1‒4, 2017.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).