Metal Oxide gas sensors for Volatile Organic Compounds detection

Characterization of novel sensing materials for Volatile Organic Compound detectionThe ability to detect, distinguish and categorize odors finds valuable uses in several fields such as automotive, industrial safety and consumer products. Volatile Organic Compounds (VOCs) are of particular relevance in these fields, as key components of many complex mixtures of gases to be detected. The electronic nose (e-nose) is a device which mimics the functionalities of the human nose through an array of gas sensors coupled with machine learning algorithms. One class of sensors used to detect low gas concentrations are the metal-oxide-semiconductor (MOX) gas sensors, sensors which change their conductivity upon gas exposure. This family of devices are generally made of a single material and are not characterized by an excellent selectivity with respect to different gases; moreover they suffer additional problems like long term stability and interference from the environment. Recent results reported in the literature show however how a combination of MOX materials can improve both selectivity and sensitivity, key figure of merit of sensor performance. Nevertheless reported results were obtained through geometries difficult to integrate and hard to produce on an industrial scale. The aim of this work is to investigate the effect of thickness and annealing processes on the performance of MOX bilayer gas sensor devices. The devices were fabricated by DC sputtering with a geometry which aims to an easy integrability. In the first part of the thesis the general theory of e-nose and gas sensor devices is discussed, with particular attention to the latest results in MOX gas sensing technology. Then, the fabrication and testing processes of the devices are fully described. At the end, the thickness and annealing experiments are described. Results show that a remarkable improvement in device response to VOCs can be achieved. It is also shown how different annealing techniques impact the device morphology in order to choose the optimal one in the devices fabrication.