Sensor array based on metal oxide modified graphene for the detection of multi-component mixed gas

This paper reports a novel nanostructure sensor array combining with back-propagation (BP) neural network toward multi-component gases detection. Tin dioxide and copper oxide modified reduced oxide graphene (rGO) were used as sensing materials toward ammonia and formaldehyde. The sensor array was fabricated via a facile hydrothermal route and layer-by-layer self-assembly method on the substrate with interdigital electrodes (IDEs). And furthermore, this work successfully achieves the recognition and prediction of components in the gas mixture of ammonia and formaldehyde through the combination of graphene-based high-performance sensor array and neural network-based signal processing technologies.