The performance of electrochemical gas sensors depends on the reactions at the three-phase boundary. In this work, a mixed-potential gas sensor containing a counter electrode, a reference electrode, and a sensitive electrode was constructed. By applying a bias voltage to the counter electrode, the three-phase boundary can be polarized. The polarization state of the threephase boundary determined the gas-sensitive performance. Taking 100 ppm ethanol vapor as an example, by regulating the polarization state of the three-phase boundary, the response value of the sensor can be adjusted from −170 to 40 mV, and the sensitivity can be controlled from −126.4 to 42.6 mV/decade. The working temperature of the sensor can be reduced after polarizing the three-phase boundary, lowering the power consumption from 1.14 to 0.625 W. The sensor also showed good stability and short response−recovery time (3 s). Based on this sensor, the Random Forest algorithm reached 99% accuracy in identifying the kind of VOC vapors. This accuracy was made possible by the ability to generate several signals concurrently. The above gas-sensitive performance improvements were due to the polarized three-phase boundary.

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A Ce 0.8 Gd 0.2 O 1.95 -based mixed potential type sensor attached with a commercially available Au paste sensing electrode material was fabricated to detect methanol. The optimum working temperature of the sensor was 545 °C, and the response value to 100 ppm methanol was −53 mV. The selectivity of the sensor was poor. The addition of a 4A molecular sieve filter layer and the method of pattern recognition were combined to improve it. Only gas molecules smaller than the pore diameter of the 4A molecular sieve were able to pass through the zeolite channel, and the selectivity coefficient of the sensor to methanol was improved by adding the filter layer. Meanwhile, there was an obvious distinction between the response and recovery times of the sensor toward methanol, ethanol, acetone, n-butanol, and n-pentanol. Next, the pattern recognition method was adopted. The relationship between the response value and the logarithm of gas concentration and the relationship between the maximum rate of the response process and the gas concentration were plotted separately. By comprehensively considering the two characteristic parameters of the response value and the maximum value of the differential response signal, the purpose of qualitative identification of gas types and quantitative analysis of gas concentrations was hopefully achieved.