Humidity-Independent Methane Gas Detection in Gd0.2La0.2Ce0.2Hf0.2Zr0.2O₂-Based Sensor Using Polynomial Regression Analysis

Chemiresistive gas sensors (CGS) are continuously being developed over other methods for detecting gas/vapor concentrations because of their simplicity of fabrication, compatibility with conventional DC circuits and high accuracy measurement convenience. However, humidity strongly influences sensing response, while the trade-off between humidity independence and gas response is one of the major barriers to limiting CGS for practical applications. In this regard, highly selective methane (CH4) gas sensor is fabricated using Gd0.2La0.2Ce0.2Hf0.2Zr0.2O2 (Ce-HEC) as a sensing material and the relative humidity (RH) effect on sensing response has been investigated. Indeed, the RH effect on the sensor response is high and can be seen in all gas concentrations at various RH levels. Therefore, humidity compensation model (HCM) is developed by fitting multivariate polynomial regression techniques to reduce the anti-interference humidity effect. HCM estimates the gas concentrations with a mean absolute percentage error of 5.81%, and a mean absolute error is 3.43 ppm. This study offers a simple and novel strategy for humidity-independent detection of gas/vapors in CGS and estimates gas concentrations with minimum error.