Abstract

AbstractSemiconductive metal‐oxide sensors suffer from cross‐sensitivities under mixed chemical condition, specifically upon mixture of multiple oxidative or reductive gases. Herein, a single bimodular sensor is demonstrated for smart differentiation of multiple oxidative analytes by relating the resistance‐metric mode to impedance‐metric mode. The sensor construct based on ZnO nanorods readily outputs three response datasets upon exposure of oxidative‐gas mixture including O2, SO2, and NO2, the resistance, real part impedance, and imaginary part impedance. The differentiative and correlated nature between these response signals allows such a single sensor platform to differentiate these oxidative gases accurately and robustly. Linear and non‐linear decision boundaries are established over a large gas‐concentration range from 2 ppm to 3% through a combination of principal component analysis and artificial neural network training. A facile user interface is demonstrated for recognition and measurement of unknown gas analytes, with the error of the predicted analyte‐concentration as low as 2%.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call