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Canine Nose-Inspired Artificial Gas Detector

It is a known fact that the sense of smell of dogs is far superior to that of humans. For many years, scientists have been attempting to create an artificial detector with a sense of smell closer to that of a dog’s nose. At present, a team has described in ACS Nano that they could imitate the sniffer of a canine by using graphene-based nanoscrolls (GNS).

The inner side of a canine’s nose is arrayed with millions of tiny capillaries, resulting in a superior sense of smell. As a large surface area is covered by the capillaries, can detect smells at very low concentrations. Taking a cue from the capillary formation inside the nose of a dog, researchers have been attempting to imitate it to develop a highly sensitive gas detector. Earlier research works have had limited success in using GNS.

GNS are graphene nanosheets rolled up in a uniform and continuous manner, and are stable at high temperatures, have a large surface area, and are durable and strong. However, it is also challenging to produce, needed a great amount of energy, and hard to scale up. Earlier research works have adopted raw graphene or modified graphene that either left a little amount of unrolled structures or aggregated and shriveled up structures, respectively, as remnants. Therefore, Yao Wang, Lei Jiang, Guofu Zhou, and their collaborators aimed to alter the graphene by using a polymer to produce GNS of higher quality.

The team produced GNS by adding poly(sodium-p-stryrenesulfonate) and adopting the freeze-drying technique to develop unaggregated, uniform structures. During investigations, the GNS were found to have a wide, tubular shape, and nearly the entire graphene was rolled up. Then, the scientists incorporated the GNS into a highly sensitive and selective gas sensor. Finally, the group noted that this technique could be prospectively applied for large-scale production.

Funding from the National Natural Science Foundation of China, the Natural Key Basic Research Program of China, the Startup Foundation from South China Normal University, the Guangdong Innovative Research Team Program, the Guangdong Provincial Key Laboratory of Optical Information Materials and Technology, the MOE International Laboratory for Optical Information Technologies, and the 111 Project is acknowledged by the authors.

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