Kinetic and Statistical Analysis of the Conductance Transient to Address the Selectivity Issue of the Wet Chemically Synthesized Tailored Nano-structured Ferrite Gas Sensors

Abstract

In the present work we have optimized the gas sensing performances of wet chemically synthesized Mg0.5Zn0.5Fe2O4 nano‐structures (in the form of nano‐powders (0‐d), nano‐tubes (1‐d), thin films (2‐d) and embedded nano‐tubes into anodized alumina) in terms of sensitivity, response/recovery times, stability and selectivity in presence of H2, CO, CH4, and N2O gases. It has been demonstrated that the change in surface morphology significantly influences the gas sensing characteristics of these semiconducting spinel ferrite sensing elements. The adsorption and desorption characteristic of the test gases during the gas sensing process are investigated by modeling the conductance transients using Langmuir adsorption isotherm. These analyses revealed that for the test gases, the values of the heat of adsorption, concentration dependence of the response time constants, and the activation energies for adsorption and desorption processes are distinctly different. It is also revealed that the principal component analysis (PCA) and discriminant factor analysis (DFA) of both the fast Fourier transform (FFT) and discrete wavelet transform (DWT) spectra of the conductance transients of these test gases have salient characteristic features. Statistical analyses in conjunction with the analyses of adsorption and desorption kinetics of a single sensing element, therefore, is beneficial in differentiating the gas type.