Scientists have designed an e-nose that could detect the presence of harmful chemicals in the air.
The team of researchers created a fluid mechanics-based chamber design for an electronic nose (e-nose) that consistently detects volatile organic compounds (VOC) at low concentrations.
VOCs are chemicals emitted as gases that can have adverse health effects. They are often found in paints, pharmaceuticals, and refrigerants, but they can also be signs of explosives, insect infestation, food spoilage, and disease.
Although VOCs can be difficult to detect, e-noses combine arrays of chemical sensors with pattern recognition techniques to recognise odours.
However, many e-noses generate different signals toward VOCs of the same concentration when the sensor is located in different parts of the “nose” chamber.
“To counteract this problem, the fluidic behaviour of the gas flow needs to be well controlled,” said author Weiwei Wu of Xidian University, China. “This ensures a uniform fluidic field and concentration of VOCs in the chamber and avoids generating any fake sensing characteristics.”
The new e-nose design features a vertical chamber that looks much like a showerhead. This promotes vertical flow as gas spreads through holes at the bottom of the device and around evenly distributed sensors.
Based on their simulation results, the researchers fabricated a Teflon chamber and measured the sensing performance of their e-nose. They compared two chambers, one with the shunt and one without.
The results showed that the chamber with the shunt device consistently performed around 1.3 times better at sensing an example VOC.
In the future, the authors plan to focus on minimising the chamber and improving the structure further to decrease response and recovery time.
“E-nose research is a highly interdisciplinary field,” said Wu. “Chemists, physicists, biologists, electronics engineers, and data scientists need to work together to solve issues including effective sensing that considers the fundamental mechanisms of absorption/desorption, algorithms that achieve precise recognition of VOCs more quickly and with lower energy consumption, and how new technologies, such as memristors, should be involved.”
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