A hybrid structure gas sensor of reduced graphene oxide (RGO) decorated graphene (RGO-Gr) is designed for ultra-low concentration ammonia detection. The resistance value of the RGO-Gr hybrid is the indicator of the ammonia concentration and controlled by effective charge transport from RGO to graphene after ammonia molecule adsorption. In this hybrid material, RGO is the adsorbing layer to catch ammonia molecules and graphene is the conductive layer to effectively enhance charge/electron transport. Compared to a RGO gas sensor, the signal-to-noise ratio (SNR) of the RGO-Gr is increased from 22 to 1008. Meanwhile, the response of the RGO-Gr gas sensor is better than that of either a pristine graphene or RGO gas sensor. It is found that the RGO reduction time is related to the content of functional groups that directly reflect on the gas sensing properties of the sensor. The RGO-Gr gas sensor with 10 min reduction time has the best gas sensing properties in this type of sensor. The highest sensitivity is 2.88% towards 0.5 ppm, and the ammonia gas detection limit is calculated to be 36 ppb.

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It is a daunting challenge to measure the concentration of each component in natural gas, because different components in mixed gas have cross-sensitivity for a single sensor. We have developed a mixed gas identification device based on a neural network algorithm, which can be used for the online detection of natural gas. The neural network technology is used to eliminate the cross-sensitivity of mixed gases to each sensor, in order to accurately recognize the concentrations of methane, ethane and propane, respectively. The neural network algorithm is implemented by a Field-Programmable Gate Array (FPGA) in the device, which has the advantages of small size and fast response. FPGAs take advantage of parallel computing and greatly speed up the computational process of neural networks. Within the range of 0–100% of methane, the test error for methane and heavy alkanes such as ethane and propane is less than 0.5%, and the response speed is several seconds.

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