Unlike large devices that consume a lot of power, these new sensors are extremely lightweight, operate at room temperature, and consume very little power. Made from “airgel” materials, known as “frozen smoke” due to their air-filled structure, they have a highly porous surface that is ideal for trapping gas molecules.
So how do they determine the culprit? By carefully shaping the airgel’s pores, researchers created a unique fingerprint detector for formaldehyde, a common but dangerous indoor air pollutant linked to respiratory diseases and even cancer. Machine learning algorithms can provide a much clearer picture of indoor air quality by separating formaldehyde from other gases in the air.
The researchers suggest the technology could be adapted to detect a wide range of hazardous substances, paving the way for wearable air quality monitors and healthcare applications.
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Source: Ferra
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