Odors are all around us, and often disperse fast—in hazardous situations like wildfires, for example, wind conditions quickly carry any smoke (and the smell of smoke) away from its origin. Sending people to check out disaster zones is always a risk, so what if a robot equipped with an electronic nose, or e-nose, could track down a hazard by “smelling” for it?
This concept motivated a recent study in Science Advances, in which researchers built an e-nose that can not only detect odors at the same speed as a mouse’s olfactory system, but also distinguish between odors by the specific patterns they produce over time when interacting with the e-nose’s sensor.
“When odorants are carried away by turbulent airflow, they get chopped into smaller packets,” says Michael Schmuker, a professor at the University of Hertfordshire in the United Kingdom. Schmuker says that these odor packets can rapidly change, which means that an effective odor-sensing system needs to be fast to detect them. And the way in which packets change—and how frequently that happens—can give clues about how far away the odor’s source is.
How the E-nose Works
The e-nose uses metal oxide gas sensors with a sensing surface heated and cooled to between 150 °C and 400 °C at up to 20 times per second. Redox reactions take place on the sensing surface when it comes into direct contact with an odorant.
The new electronic nose is smaller than a credit card, and includes several sensors such as the one on the right.Nik Dennler et al.
The e-nose is smaller than a credit card, with a power consumption of only 1.2 to 1.5 watts (including the microprocessor and USB readout). The researchers built the system with off-the-shelf components, with custom-designed digital interfaces to allow odor dynamics to be probed more precisely when they encounter the heated electrodes making up the sensing surface. “Odorants flow around us in the air and some of them react with that hot surface,” says Schmuker. “How they react with it depends on their own chemical composition—they might oxidize or reduce the surface—but a chemical reaction takes place.”
As a result, the resistance of the metal oxide electrodes changes, which can be measured. The amount and dynamics of this change are different for different combinations of odorants and sensor materials. The e-nose uses two pairs of four distinct sensors to build a pattern of resistance response curves. Resistance response curves illustrate how a sensor’s resistance changes over time in response to a stimulus, such as an odor. These curves capture the sensor’s conversion of a physical interaction—like an odor molecule binding to its surface—into an electrical signal. Because each odor generates a distinct response pattern, analyzing how the electrical signal evolves over time enables the identification of specific odors.
“We discovered that rapidly switching the temperature back and forth between 150°C and 400°C about 20 times per second produced distinctive data patterns that made it easier to identify specific odors,” says Nik Dennler, a dual Ph.D. student at the University of Hertfordshire and Western Sydney University. By building up a picture of how the odorant reacts at these different temperatures, the response curves can be plugged into a machine learning algorithm to spot the patterns that relate to a specific odor.
While the e-nose does not “sniff” like a regular nose, the periodic heating cycle for detecting odors is reminiscent of the periodic sniffing that mammals perform.
Using the E-nose in Disaster Management
A discovery in 2021 by researchers at the Francis Crick Institute in London and the University College London showed that mice can discriminate odor fluctuations up to 40 times per second—contrary to a long-held belief that mammals require one or several sniffs to obtain any meaningful odor information.
In the new work—conducted in part by the same researchers behind the 2021 discovery—the researchers found that the e-nose can detect odors as quickly as a mouse can, with the ability to resolve and decode odor fluctuations up to 60 times per second. The e-nose can currently differentiate between 5 different odors when presented individually or in a mixture of two odors. The e-nose could detect additional odors if it is trained to do so.
“We found it could accurately identify odors in just 50 milliseconds and decode patterns between odors switching up to 40 times per second,” says Dennler. For comparison, recent research in humans suggests the threshold for distinguishing between two odors binding to the same olfactory receptors is about 60 ms.
The small scale and moderate power requirements could enable the e-nose to be deployed in robots used to pinpoint an odor’s source. “Other fast technologies exist, but are usually very bulky and you would need a large battery to power them,” says Schmuker. “We can put our device on a small robot and evaluate its use in applications that you use a sniffer dog for today.”
“As soon as you’re driving, walking, or flying around, you need to be really fast at sensing,” says Dennler. “With our e-nose, we can capture odor information at high speeds. Primary applications could involve odor-guided navigation tasks, or, more generally, collecting odor information while on the move.”
The researchers are looking at using these small e-nose robots in disaster management applications, including locating wildfires and gas leaks, and finding people buried in rubble after an earthquake.
Reference: https://ift.tt/iXzf2cp
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Digital data is converted to analog voltages [left]. These are effectively multiplied by flash memory cells [blue], summed, and converted back to digital data [bottom].Analog Inference
Future systems from Sageance will be made up of 3D-stacked analog chips linked to a processor and memory through an interposer that follows the universal chiplet interconnect (UCIe) standard.Analog Inference
