Though most human noses can detect suspicious smells at relatively high levels, they're not always able to discern every single scent. Researchers from the University of California - Berkeley, however, have developed an “electronic nose” that can pick up on the gases emitted by expired food or food allergens which they claim is “better than human noses.”
The new device is made up of 16 small gas-detecting sensors that identify slight variations in gas molecules including those of common food allergens like walnuts and peanuts that could be life-threatening for those with allergies.
“You can think of it like a set of digital taste buds, where each sensor on this chip responds uniquely to the various gas molecules presented to it,” says Carla Bassil, study lead author and PhD student in electrical engineering and computer sciences at UC Berkeley.
There are hurdles to overcome with the difficulty in combining different gas-detecting sensors onto a single computer chip, compared to the simple one found in standard home carbon monoxide detectors which are programmed to sense a single gas.
In order to meet this challenge, Bassil used carbon nanotubes that form layers one one-hundredth the thickness of a human hair (instead of metal oxides that need to heat up) as the conduction material.
The carbon nanotubes are highly sensitive at room temperature, enabling Bassil to select a larger range of gas-sensitive materials, including those that might deteriorate at high temperatures – polymers are one example. She constructed the sensor simply by drop casting (depositing a small film) instead of more laborious techniques.
With the aid of a machine learning model, the electric nose registers the response of each substance related to a particular food or scent profile.
“Each of these 16 sensors has a different sensing film on it, and it works by converting chemical reactions between the sensor surface and the gas molecule into electrical signals,” says Bassil.
She trained the model to recognize the response profiles associated with seven foods: strawberry, blueberry, banana, walnut, hazelnut, cashew and peanut as well as the scent of fresh raw chicken, milk and eggs, and when they have been sitting out at room temperature for 24 hours and 48 hours.
“The idea is that we can use the relative selectivity of the gas sensors, paired with the pattern recognition abilities of machine learning, to sort out which gas fingerprint is associated with each food,” Bassil says. “The result is a sensor chip that is far more sensitive and far more objective than any human nose can be.”
A walnut fragment of 0.05 grams (or one one-hundredth of a standard shelled walnut) was able to be detected by the nose, but Bassil has not yet researched whether it is sensitive enough to discern allergens when other gas molecules co-exist, such as in a cake or salad or when contaminated food is refrigerated with other foods.
“I think ‘smart’ fridges – which come with sensors that you can control on your phone – would be a great application for this kind of technology,” says Bassil, “How great would it be if your fridge could tell you, ‘Hey, your broccoli’s going to go bad soon, so you should probably eat that’? Or, ‘Your chicken is on its last day’?”.
A paper on the research was recently published in the journal Science Advances.
And funnily enough or not, I snacked on some walnuts while working on this piece and discovered a moldy piece that went down the hatch before I had a chance to eject. Yuck.
