Funded Project (2022-2024) Engineered olfaction system with massively parallel optical readout (EMPOR)
At present, no existing technology can match the extraordinary sensitivity and specificity of natural olfactory systems. The EMPOR project aims to develop an advanced “artificial nose” that emulates the mammalian olfaction system's ability to detect and differentiate complex odor mixtures. The key idea lies in employing a significantly larger array of sensors than are currently used in existing electronic noses, combined with an innovative optical and parallel readout system that circumvents the complexities of traditional electrical sensor arrays. This approach promises to significantly improve the ability to discern odors.
In the mammalian olfaction system, molecular odorants are initially detected by olfactory receptors (ORs). Mammals typically possess many different kinds of ORs, with dogs having about 1,300 and humans around 400. The combination of responses from different ORs enables the discrimination of a very large number of molecules (smells). Signal processing the response from these sensors is another important ingredient in our sense of smell. While humans may not have as many OR types as some animals, humans compensate this with a large number of glomeruli, providing sophisticated olfactory input to the brain for interpreting signals. In contrast, conventional artificial electronic noses typically contain only 5-20 sensors, much less than mammalian olfactory receptors, and thus have low selectivity.
Our approach introduces several novel concepts. First, we utilize high-throughput techniques to grow nanostructured materials with an extensive surface-to-volume ratio for enhanced binding of analytes. We are able to reach more than thousands of distinct sensing components in a sensor array with a simple physical vapor deposition technique. Most importantly, we implement an optical read-out system where the modified electrical response of each sensing unit generates unique optical signals (fingerprints) that are read out optically. This allows for a much larger array than has been possible to date. Finally, we use advanced pattern recognition techniques to analyze the sensor outputs and optimize the way the sensors are arranged.
This project aims to significantly advance the ability of artificial noses to detect smells and odors from complex mixtures. Potential applications of such a system are vast, ranging from environmental monitoring to medical diagnostics, where there is a critical need for rapid, accurate analysis of air quality or a patient’s breath. Our goal is to develop the technology that hopefully will allow artificial noses to begin to rival natural olfactory systems.
