Interdisciplinary KIT Research Group Develops and Tests Artificial Odour Detection by Sensors Based on Novel Material Combinations
In nature, plant scents attract insects, for example. But they are also used in industry, for example in the production of perfumes and aromas. In order to distinguish the scents of mint in particular reliably, quickly and objectively, researchers at the Karlsruhe Institute of Technology (KIT) have developed an electronic nose with an artificial sense of smell in an interdisciplinary collaboration: With high precision, it can recognise different types of mint - making it suitable for applications ranging from pharmaceutical quality control to the observation of mint oil as an environmentally friendly bioherbicide.
"So far, research knows of an estimated 100,000 different biological compounds through which neighbouring plants interact with each other or control other organisms such as insects," says Professor Peter Nick from the KIT Botanical Institute. "These connections are very similar in plants of the same genus." A classic example in the plant world, he says, is mint, where the different varieties have very species-specific scents. The industrial monitoring of mint oil in particular is subject to strict legal regulations to avoid counterfeiting, is time-consuming and requires a lot of skill, the scientist says. A new electronic nose based on sensors with combined materials, which researchers from the Botanical Institute, the Institute for Functional Interfaces (IFG), the Institute for Microstructure Technology (IMT) and the Light Technology Institute (LTI) of KIT have jointly developed and already tested with six different types of mint, is to provide support.
Electronic nose based on biological model
In the development of the electronic nose, the entire research team orientates itself as far as possible on the biological model: the odour cells, which in humans transmit information to the brain via electrical impulses, are replaced by a total of twelve special sensors (Quartz Crystal Microbalance, or QCM sensors for short). These consist of two electrodes with a quartz crystal. Such components are also installed in mobile phones, for example, as they guarantee high accuracy of mobile phone frequencies at low cost. "The scents of the mint are deposited on the surface of the sensors. This changes their resonance frequency and we get a reaction to the respective scent," explains Professor Christof Wöll from the IFG. Scents consist of organic molecules in different compositions. To enable the new sensors to pick them up, the IFG researchers used twelve special sensor materials, including the metal-organic frameworks (MOFs) developed at the IFG. "These materials are highly porous and particularly well suited for sensor applications because they can absorb many molecules like a sponge," says Wöll. "By combining the sensors with the different materials, we virtually interconnect a neuronal network."
Training with six types of mint through machine learning
The scientists tested the electronic nose with six different types of mint - including classic peppermint, horse mint and catnip. "Using different machine learning methods, we train the sensors so that they can create the fingerprint of the respective scent from the collected data and thus distinguish the scents from each other," explains Wöll. After each fragrance sample, the nose is flushed with carbon dioxide (CO2) for about half an hour so that the sensors regenerate.
The results of the interdisciplinary research team have shown that the electronic nose with QCM sensors can assign mint scents to a species with high specificity. In addition, it is a user-friendly, reliable and cost-effective alternative to conventional methods such as mass spectrometry, says the scientist. For further development, the focus is on sensors that regenerate more quickly and can then pick up odours again. Furthermore, the researchers from the IFG are focusing on MOF materials in order to design them for other areas of application, such as artificial odour detection in medical diagnostics.
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