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Open AccessArticle

A Gas Mixture Prediction Model Based on the Dynamic Response of a Metal-Oxide Sensor

Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
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Author to whom correspondence should be addressed.
Micromachines 2019, 10(9), 598; https://doi.org/10.3390/mi10090598
Received: 9 August 2019 / Revised: 29 August 2019 / Accepted: 10 September 2019 / Published: 11 September 2019
(This article belongs to the Special Issue Advanced MEMS/NEMS Technology, Volume II)
Metal-oxide (MOX) gas sensors are widely used for gas concentration estimation and gas identification due to their low cost, high sensitivity, and stability. However, MOX sensors have low selectivity to different gases, which leads to the problem of classification for mixtures and pure gases. In this study, a square wave was applied as the heater waveform to generate a dynamic response on the sensor. The information of the dynamic response, which includes different characteristics for different gases due to temperature changes, enhanced the selectivity of the MOX sensor. Moreover, a polynomial interaction term mixture model with a dynamic response is proposed to predict the concentration of the binary mixtures and pure gases. The proposed method improved the classification accuracy to 100%. Moreover, the relative error of quantification decreased to 1.4% for pure gases and 13.0% for mixtures. View Full-Text
Keywords: metal-oxide sensors; dynamic response; temperature modulation; mixture gas prediction metal-oxide sensors; dynamic response; temperature modulation; mixture gas prediction
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MDPI and ACS Style

Wen, W.-C.; Chou, T.-I.; Tang, K.-T. A Gas Mixture Prediction Model Based on the Dynamic Response of a Metal-Oxide Sensor. Micromachines 2019, 10, 598.

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