Tunable Humidity-Sensing Performance of Graphene Oxide With Leaf-Vein-Like Multiwall Carbon Nanotube Conductive Networks

In this study, we report the humidity-sensing performance of 1,6-hexanediamine modified graphene oxide (HAGO) and functionalized multiwall carbon nanotube (fMWCNT) composites. The negatively charged fMWCNTs are randomly attached to the surface of positively charged HAGO (so-called electrostatic self-assembly), forming a leaf-vein-like conductive network. The relative resistance response of fMWCNTs/HAGO humidity sensors can be well-tuned by varying the content of fMWCNTs. The results demonstrate that the sensor based on 1:4 mass ratio of fMWCNTs/HAGO composite possesses the high relative resistance response, good repeatability and excellent stability. The decrease of mass proportion of fMWCNTs can result in the decrease of response time as well as hinder the recovery process. The resistance change of fMWCNTs/HAGO sensors over a wide range of relative humidity (35-95%) can be well fitted with the Henry-clustering model.

Automated summary

This study focuses on the humidity-sensing performance of 1,6-hexanediamine modified graphene oxide and functionalized multiwall carbon nanotube composites. The relative resistance response of the sensors can be tuned by varying the content of fMWCNTs, with a 1:4 mass ratio showing high response, repeatability, and stability. The decrease in mass proportion of fMWCNTs is found to lower response time and hinder the recovery process, with the resistance change over a wide range of humidity levels fitting well with the Henry-clustering model.