期刊
NANOMATERIALS
卷 13, 期 5, 页码 -出版社
MDPI
DOI: 10.3390/nano13050917
关键词
p-n junctions; ZnO; reduced graphene oxide; rGO; NO2 sensing
In this study, ZnO nanoparticles were loaded with 0.1% to 4% rGO using a hydrothermal method and evaluated as NO2 gas chemiresistors. The doping ratio was found to affect the sensing properties, with the conductivity type of ZnO/rGO changing from n-type to mixed n/p-type and finally to p-type. Different sensing regions exhibited different sensing characteristics, and the p-n heterojunction ratio played a key role in the optimal response condition.
Nanoscale heterostructured zinc oxide/reduced graphene oxide (ZnO/rGO) materials with p-n heterojunctions exhibit excellent low temperature NO2 gas sensing performance, but their doping ratio modulated sensing properties remain poorly understood. Herein, ZnO nanoparticles were loaded with 0.1 similar to 4% rGO by a facile hydrothermal method and evaluated as NO2 gas chemiresistor. We have the following key findings. First, ZnO/rGO manifests doping ratio-dependent sensing type switching. Increasing the rGO concentration changes the type of ZnO/rGO conductivity from n-type (<0.6% rGO) to mixed n/p -type (0.6 similar to 1.4% rGO) and finally to p-type (>1.4% rGO). Second, interestingly, different sensing regions exhibit different sensing characteristics. In the n-type NO2 gas sensing region, all the sensors exhibit the maximum gas response at the optimum working temperature. Among them, the sensor that shows the maximum gas response exhibits a minimum optimum working temperature. In the mixed n/p-type region, the material displays abnormal reversal from n- to p-type sensing transitions as a function of the doping ratio, NO2 concentration and working temperature. In the p-type gas sensing region, the response decreases with increasing rGO ratio and working temperature. Third, we derive a conduction path model that shows how the sensing type switches in ZnO/rGO. We also find that p-n heterojunction ratio (n(p-n)/n(rGO)) plays a key role in the optimal response condition. The model is supported by UV-vis experimental data. The approach presented in this work can be extended to other p-n heterostructures and the insights will benefit the design of more efficient chemiresistive gas sensors.
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