Science & Technology, UK (Commonwealth Union) – A team of researchers at the University of Cambridge has engineered a sensor utilizing ‘frozen smoke’ technology, bolstered by artificial intelligence algorithms, capable of detecting formaldehyde in real-time at remarkably low concentrations, as low as eight parts per billion. This sensitivity surpasses the capabilities of most existing indoor air quality sensors.
These sensors, constructed from highly porous aerogel materials, leverage precisely tailored pore structures to discern the unique signature of formaldehyde, a prevalent indoor air pollutant, even at ambient room temperatures. Their proof-of-concept, low-power design suggests adaptability for detecting various hazardous gases and potential miniaturization for applications in wearable technology and healthcare. These findings have been detailed in the journal Science Advances.
Indoor air pollution, primarily driven by volatile organic compounds (VOCs), can lead to discomfort such as eye irritation, throat irritation, watery eyes, and breathing difficulties at heightened levels. Elevated concentrations of VOCs can exacerbate asthma symptoms and, with prolonged exposure, may contribute to certain cancers.
Researchers of the study emphasized that Formaldehyde, a ubiquitous VOC, emanates from common household items including pressed wood products (like MDF), wallpapers, paints, and some synthetic textiles. Although the emission levels from these sources are generally low, accumulation over time, particularly in environments like garages where formaldehyde-emitting products are commonly stored, can pose risks.
A report from Clean Air Day in 2019 revealed that approximately one-fifth of UK households exhibited notable concentrations of formaldehyde, with 13% exceeding the recommended limits set by the World Health Organization (WHO).
Professor Tawfique Hasan of the Cambridge Graphene Centre, leading the research, highlighted the concerning impact of VOCs like formaldehyde on health, even at minimal concentrations. However, existing sensors lack the sensitivity and selectivity necessary to differentiate between VOCs with varying health implications.
Zhuo Chen, the primary author of the paper, emphasized the goal of creating a compact, low-power sensor capable of specifically detecting formaldehyde at trace levels.
To achieve this, the team turned to aerogels, colloquially known as ‘liquid smoke’ due to their predominantly air-based composition exceeding 99% by volume. Leveraging the porous nature of aerogels, gases can freely permeate through them. By meticulously tailoring the morphology of these pores, aerogels demonstrate exceptional efficacy as sensors, as indicated by researchers of the study.
Collaborating with colleagues from Warwick University, researchers from Cambridge University refined the composition and arrangement of aerogels to heighten their sensitivity to formaldehyde. They transformed these aerogels into filaments approximately three times the width of a human hair. The team utilized a process where they 3D printed lines of a paste composed of graphene, a two-dimensional carbon form, then freeze-dried the graphene paste to create pores within the final aerogel structure. These aerogels were augmented with minute semiconductors called quantum dots.
The resultant sensors exhibited the capability to detect formaldehyde at concentrations as minimal as eight parts per billion, equating to 0.4 percent of the deemed safe level in UK workplaces. Moreover, these sensors operated efficiently at room temperature, with exceptionally low power consumption.
“Traditional gas sensors need to be heated up, but because of the way we’ve engineered the materials, our sensors work incredibly well at room temperature, so they use between 10 and 100 times less power than other sensors,” Chen explained.
For selectivity enhancement the researchers applied machine learning algorithms for sensors. The algorithms were shown to identify the ‘fingerprint’ of various gases, making it possible for the sensor to differentiate a formaldehyde fingerprint from other VOCs.
“Existing VOC detectors are blunt instruments – you only get one number for the overall concentration in the air,” explained Hasan. “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.”
The scientists suggest that the identical method could potentially be employed to fabricate sensors capable of identifying various other VOCs. In principle, a device akin to a typical household carbon monoxide detector could integrate numerous sensors, furnishing instantaneous data on various perilous gases. The co-author Professor Julian Gardner from Warwick University indicated that at Warwick, they are advancing an economical multi-sensor framework that will integrate these novel aerogel substances and, paired with AI algorithms, discern different VOCs.
“By using highly porous materials as the sensing element, we’re opening up whole new ways of detecting hazardous materials in our environment,” added Chen.
Researchers across the world in recent year have made a significant focus on items used on daily basis by examining how safe they are. With new detection methods and possible safety levels will make it possible for researchers exploring this field to make significant contributions on environmental toxins.
