Capacitive polymer sensors: Factors influencing performance and design principles

Abstract

Capacitive polymer sensors present a promising approach for machine olfaction arrays capable of detecting and classifying various analytes. In this study, a comprehensive analysis of factors influencing capacitive vapor sensors is performed. An in-depth analysis of performance of sensing polymers with a wide range of solubility interactions and dielectric constants is performed providing a foundation for sensor design principles. Unique frequency-dependent signal-to-noise behavior was observed for each polymer-analyte pair due to variations in polarization mechanisms, which was in turn used to tune the array for a better sensitivity. Film thickness and background humidity on array sensitivity was also explored. Design principles based on this study are used to optimize sensor arrays for the classification and quantification of analytes exhibiting distinct solubility interactions (alcohol, ketone, ester, and two hydrocarbons). Electrochemical impedance spectroscopy analysis provides valuable insight into the different physical processes and polarization mechanisms for each sensing polymer. The design principles explored have broad implications for other dielectric-based sensing systems, including integrated circuit-based arrays such as field-effect transistors.