Explainable AI (XAI) is being used to reveal how chemical sensors discriminate among various odourant molecules, in a new study. The findings may help guide the selection of materials for developing high-performance chemical sensors. It shows promise both for improving the performance of artificial olfaction as well as advancing understanding of human olfactory mechanisms. (Words: National Institute for Materials Science, Japan).
Olfactory sensors, which mimic the human sense of smell, use multiple chemical sensors to detect odourant molecules and employ AI to classify and identify them. However, current AI-assisted artificial olfaction has yet to reach practical application due to the limited sensitivity and discrimination accuracy of existing chemical sensors. Addressing this challenge will require higher-performance chemical sensors, particularly through the development of receptor materials capable of more effectively detecting odourant molecules.
In conventional artificial olfaction, AI has classified and identified odourant molecules without a full understanding of which receptor materials respond to which molecules. Revealing the response characteristics of specific receptor materials will enable the development of materials for discriminating target odourants and the selection of receptor materials that achieve more accurate odour discrimination.
NIMS measured the responses of 94 odourant molecules using an MSS (membrane-type surface stress sensor) equipped with 14 receptor materials and analyzed the data with explainable AI (XAI), a technique that visualizes which parts of the data the AI relies on when discriminating among odourant molecules.
The analysis revealed that the key portions of sensor responses used for identification vary depending on the specific combinations of odourant molecules and receptor materials. For example, receptor materials containing aromatic rings were found to be important for identifying aromatic molecules. This approach is expected to enable efficient selection of receptor materials tailored to target odourant molecules and guide the development of materials capable of identifying molecules that are otherwise difficult to detect. In addition, by revealing not only how the AI discriminates but also on what basis it makes predictions, XAI may offer clues to understanding the mechanisms of odours and human olfaction.
