This 3D-printed dog nose can detect explosives

(Image credit: Robert Rathe)

Fluid dynamics researchers in the US have discovered that adding a 3D-printed dog nose onto the end of the nozzle of an explosives detector significantly improves its performance.

Matthew Staymates, who led the research at the US National Institute of Standards and Technology, was inspired by the "active sniffing" technique that dogs perform when they want to smell something. According to high-speed imagery, dogs first exhale, then inhale sharply to fill their nose with aromas, ready for decoding by about 300 million receptor cells.

So, using a 3D printer, Staymates designed a nozzle for an explosives detector that mimicked the external features of the nose of a female labrador retriever - including the shape, direction and spacing of the nostrils.

A labrador's amazingly developed nose

A labrador's amazingly developed nose

Increasingly Large Distances

In testing, the air-sampling performance of the 'active sniffing' dog nose was between four and 18 times better than a traditional detector that relies on continuous suction, depending on the distance to the vapour source.

“The dog is an active aerodynamic sampling system that literally reaches out and grabs odorants,” explained Staymates. “It uses fluid dynamics and entrainment to increase its aerodynamic reach to sample vapors at increasingly large distances. Applying this bio-inspired design principle could lead to significantly improved vapor samplers for detecting explosives, narcotics, pathogens—even cancer.”

They then equipped a commercially-available detector with a bio-inspired 3D-printed inflow that allowed it to sniff like a dog, rather than inhaling once every ten seconds as it would normally do. That switch resulted in a 16-fold improvement in odour detection at a distance of four centimetres.

Amazing Chemical Sampler

“Their incredible air-sampling efficiency is one reason why the dog is such an amazing chemical sampler,” Staymates said. “It’s just a piece of the puzzle. There’s lots more to be learned and to emulate as we work to improve the sensitivity, accuracy and speed of trace-detection technology.”

The full details of the work were published in the journal Scientific Reports. 

Duncan Geere
Duncan Geere is TechRadar's science writer. Every day he finds the most interesting science news and explains why you should care. You can read more of his stories here, and you can find him on Twitter under the handle @duncangeere.
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