PEDOT:PSS/QCM-based multimodal humidity and pressure sensor

Abstract

A room-temperature multimodal sensor composed of PEDOT:PSS deposited on an AT-cut quartz crystal microbalance (QCM) crystal has been fabricated. The nonlinear resistive and frequency sensor responses are deconvolved using an articial neural network (ANN), which allows the single sensor to function simultane- ously as a relative humidity (RH) sensor and a pressure sensor using only two electrodes. We demonstrate that the predictive ability of the sensor is highly in uenced by the data used to train the ANN. When training sets are tailored to resemble the operating conditions of the sensor, the sensor achieves an average resolution of < 3% RH from 0-100% RH, even after H2O saturation occurs on the surface. Our results indicate that ANNs show strong promise for improving the resolution of low cost gas sensors and for expanding the range of environmental conditions in which a given sensor can operate.