First-order time-derivative readout of epitaxial graphene-based gas sensors for fast analyte determination

Abstract

For many applications, gas sensors need to be very sensitive, selective and exhibit a good stability. Moreover, they should also be cheap and small, and allow a fast response time. Usually, sensors are optimized for specific applications with a compromise between the mentioned criteria. Here, we show a method that allows very sensitive, but rather slow, graphene metal oxide hybrid sensors to be used in a much faster and more effective way with a focus on targeting trace level concentrations of some common toxic air pollutants. By exploiting the first-order time-derivative of the measured resistance signal after a concentration step, the response peak is achieved much faster, while also being more robust against sensor exposure and relaxation times, and concomitantly maintaining the very high sensitivities inherent to graphene. We propose to use this method to generate an additional signal to allow using sensors that are normally rather slow in applications where steep concentration changes need to be detected with much faster time constants.

Keywords

• Epitaxial graphene on SiC
• Chemical gas sensor
• First-order time-derivative signal
• Fast sensor readout
• Air quality monitoring