Pattern Recognition Using Chemical Sensor for Identification of Solid Materials by Responses to Multiple Probe Gases

A conventional approach to the analysis of solid materials generally focuses on their physical and chemical properties and thus requires a corresponding analysis method. Recently, we have developed a novel sensing approach for materials analysis based on pattern recognition using chemical sensor arrays. Since the sensing responses of a solid receptor material to gaseous molecules are unique to the combination of the solid materials and the gaseous molecules, solid materials can be identified by analyzing their response patterns to known “probe gases.” Here, we demonstrate the identification of solid materials with their chemical or physical properties using this approach. Using a nanomechanical sensor as a sensing platform, we succeeded in simultaneously identifying differences between organic polymers and inorganic nanoparticles and their respective hydrophilicity. Moreover, we even identified the differences in polymer blends, which contain different amounts of plasticizers. Any kind of gaseous and volatile molecules can be utilized as a probe gas, and hence, the number of response patterns can be tremendously increased by simply increasing the number of probe gases. Combined with a machine learning-based pattern recognition model, the present approach can be applied to a wide range of solid material analyses with high accuracy. This approach is expected to have potential applications in various fields such as materials science, chemistry, food, and environment.