A team of engineers and the University of Cambridge have developed ultrasensitive sensors from a highly porous, graphene-based airgel called “frozen smoke”. The study was published in the scientific journal magazine Science Advances (SciAdv).
The new sensor uses artificial intelligence (AI) tools to detect formaldehyde, a common indoor air pollutant.
Formaldehyde is a common volatile organic compound (VOC) emitted from household products, including pressed wood products (such as MDF), wallpaper and paint, and some synthetic fabrics.
“Formaldehyde and other VOCs can cause serious health problems with long-term exposure, even at low concentrations, but current sensors do not have the sensitivity or selectivity to distinguish compounds that have different effects on the body,” said study leader Professor Tawfik Hasan.
Engineers 3D printed lines of graphene and then froze the material to create the airgel structure.
The off-the-shelf sensors were able to detect formaldehyde at concentrations as low as eight parts per billion, 0.4% of the safe level. According to the creators, the devices consume 10-100 times less energy than analogues.
To increase selectivity, researchers incorporated machine learning algorithms into sensors. The AI is trained to detect traces of various gases so that the sensor can distinguish traces of formaldehyde from other VOCs.
The technology could be adapted to detect carbon monoxide and other volatile toxins, according to the authors of the development.
Previous scientists was created Medical sensor powered by sound vibrations.