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Gizmodo, Fortune, Time: Scientists Have Turned Gum Into a Carbon Nanotube-Loaded Sensor

December 4, 2015 — 

Malcolm Xing, a professor in the departments of mechanical engineering, and biochemistry and genetics, has developed a revolutionary technology that is creating a lot of buzz around the globe because it involves such a an unusual piece of equipment – chewing gum.

As Gizmodo writes:

It sounds like it could be something that Q hands to Bond, but researchers have developed a way to incorporate carbon nanotubes into chewing gum so that the sticky mass can be used as a stretchable, bendable medical sensor.

A team of researchers from the University of Manitoba in Winnipeg chewed Doublemint gum for 30 minutes, soaked it in ethanol to make sure it was clean, then loaded it with carbon nanotubes. The resulting blob was still flexible and bendable and, thanks to the fact that carbon nanotubes can conduct electricity, able to be used as a sensor.

As Fortune writes:

Pricing out at under 3 bucks a piece, the gum sensors are much cheaper than other alternatives engineering professor Malcolm Xing says he’s tried.

It’s the latest thrifty find in a rapidly-evolving $10 billion-plus biotech market that’s shifting away from bulky machines towards stretchy tattoo-like monitors, fingertip-sized electrical boards, injectable dyes, and ingestibles.

And for Xing, all it required was a trip to the local supermarket.

As Time writes:

Why might such a thing be needed? Sensors in wearables are typically made of metal and can stop working if they are twisted too much, the American Chemical Society says in a statement about the research. To prevent this, some researchers have created sensors from plastics, but have found they are less sensitive at making measurements.

This story was also reported on Yahoo News, in the Daily Mail, Food World News, Singapore NewsLab Canada and many others.

Xing is also principal investigator at the Children’s Hospital Research Institute of Manitoba.

Research at the University of Manitoba is partially supported by funding from the Government of Canada Research Support Fund.

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