It is well known that dogs have a better sense of smell than humans. For years, researchers have been trying to develop an artificial detector that is just as good as a canine's nose. Now, one group reports in ACS Nano that they were able to mimic a dog's sniffer with graphene-based nanoscrolls.
The inside of a dog's nose is lined with millions of tiny capillaries, which creates a super-sensitive sense of smell. Since the capillaries cover such a large surface area, they can detect odors at extremely low concentrations. Drawing inspiration from the capillary structure in the dog nose, scientists have been trying to mimic it to create a sensitive gas detector. Previous studies have had some success in using graphene-based nanoscrolls (GNS), which are nanosheets of graphene rolled up in continuous and uniform manner. These nanoscrolls have a large surface area, are stable at high temperatures, and are strong and durable. But they are also difficult to manufacture, consume a lot of energy and difficult to scale up. And past studies have used raw graphene or modified graphene that either left behind some unrolled structures, or shriveled up and aggregated, respectively. So Yao Wang, Lei Jiang, Guofu Zhou and colleagues wanted to modify the graphene with a polymer to make high-quality nanoscrolls.
The group prepared graphene-based nanoscrolls with the addition of poly(sodium-p-stryrenesulfonate) using the freeze-drying method to create uniform, unaggregated structures. Upon examination, the nanoscrolls had a wide, tubular shape, and almost all of the graphene was rolled up. The researchers then incorporated the nanoscrolls into a gas sensor, which was highly selective and sensitive. Lastly, the team notes that this method has the potential for large-scale production.
The authors acknowledge 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.
The paper's abstract will be available on March 7 at 8 a.m. Eastern time here:
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