A High-Precision Hydrogen Sensor Array Based on Pt-Modified SnO2 for Suppressing Humidity and Oxygen Interference

Humidity and oxygen have significant impacts on the accuracy of hydrogen detection, especially for metal oxide semiconductor sensors at room temperature. Addressing this challenge, this study employs a screen-printed 1 × 2 resistive sensor array made from an identical 1 wt.% platinum-modified tin oxide nanoparticle material. Fabrication variability between the two sensing elements was intentionally leveraged to enhance array output differentiation and information content. Systematic hydrogen-sensing tests were conducted on the array under diverse oxygen and moisture conditions. Three distinct feature types—the steady-state value, resistance change, and area under the curve—were extracted from the output of each array element. These features, integrated with their quotient, formed a nine-feature vector matrix. A multiple linear regression model based on this array output was developed and validated for hydrogen prediction, achieving a coefficient of determination of 0.95, a mean absolute error of 125 ppm, and a mean relative standard deviation of 7.07%. The combined information of the array provided significantly more stable and precise hydrogen concentration predictions than linear or nonlinear models based on individual sensor features. This approach offers a promising path for mass-producing highly interference-resistant, precise, and stable room-temperature hydrogen sensor arrays.