'Frozen smoke' sensors detect indoor pollutants

Researchers from the University of Cambridge have developed a sensor made from ‘frozen smoke’ that uses artificial intelligence techniques to detect formaldehyde in real time at concentrations beyond the sensitivity of most indoor air quality sensors. The sensor was made from porous materials known as aerogels; ultra-light materials that are sometimes referred to as “liquid smoke”, as they are more than 99% air by volume. By precisely engineering the shape of the holes in the aerogels, the sensors were able to detect the fingerprint of formaldehyde, a common indoor air pollutant, at room temperature.

The sensors, which require minimal power, could be adapted to detect a range of hazardous gases and could also be miniaturised for wearable and healthcare applications. Volatile organic compounds (VOCs) are a source of indoor air pollution and can cause watery eyes, burning in the eyes and throat, and difficulty breathing at elevated levels. Formaldehyde is a common VOC and is emitted by household items such as pressed wood products, wallpapers and paints, and some synthetic fabrics. The levels of formaldehyde emitted by these items are low, but can build up over time.

Professor Tawfique Hasan from the Cambridge Graphene Centre said current sensors don’t have the sensitivity or selectivity to distinguish between VOCs that have different impacts on health. The paper’s first author, Zhuo Chen, said the researchers wanted to develop a sensor that is small and doesn’t use much power, but can selectively detect formaldehyde at low concentrations.

The open structure of aerogels allows gases to move in and out. By engineering the shape of the holes, the aerogels can act as effective sensors. The researchers optimised the composition and structure of the aerogels to increase their sensitivity to formaldehyde, making them fit into filaments three times the width of a human hair. The researchers then 3D printed lines of a paste made from graphene and freeze-dried the graphene paste to form the holes in the final aerogel structure. The aerogels also incorporated small semiconductors known as quantum dots.

Chen said that traditional sensors need to be heated up, but the new sensors work well at room temperature because of the way the researchers engineered the materials. The new sensors reportedly use between 10 and 100 times less power than other sensors. The researchers also incorporated machine learning algorithms in the sensors, training the algorithms to detect the ‘fingerprint’ of different gases, so that the sensor was able to distinguish the fingerprint of formaldehyde from other VOCs.

“Existing VOC detectors are blunt instruments — you only get one number for the overall concentration in the air. By building a sensor that can detect specific VOCs at very low concentrations in real time, it can give home and business owners a more accurate picture of air quality and any potential health risks,” Hasan said.

The researchers’ technique could be used to develop sensors to detect other VOCs; theoretically, a device the size of a single household carbon monoxide detector could incorporate multiple different sensors within it, providing real-time information about a range of different hazardous gases.

“By using highly porous materials as the sensing element, we’re opening up whole new ways of detecting hazardous materials in our environment,” Chen said.

The research findings were published in the journal Science Advances.

Image credit: iStock.com/alexeyrumyantsev

This is a modified version of a news item published by the University of Cambridge under CC BY-NC-SA 4.0. This version is similarly licensed under CC BY-NC-SA 4.0. The original version of the news item can be accessed here.