Pattern recognition of solid materials by multiple probe gases

A pattern recognition-based chemical sensor array is an efficient approach to discriminating odours or complex mixture of gaseous molecules. In such an approach, solid materials are coated on surfaces of sensors as probe receptors, and gaseous molecules are exposed to those sensors as targets. Here, we propose the reverse approach, that is, gaseous molecules as probes and solid materials as targets, leading to pattern recognition of solid materials. Using a nanomechanical sensor as an example of sensing platform, we have demonstrated that this approach can discriminate polymers with different molecular weights as well as those having slightly different functional groups evaluated through detailed classification using support vector machine in addition to principal component analysis and linear discriminant analysis. Classification of those target solid materials with 100% accuracy has been achieved with some specific combinations of the probe gases. Since any kind of gaseous molecules and any kind of chemical sensors can be utilized as the probe and sensing platform, respectively, this study will open a new horizon of comprehensive analysis of solid materials through a pattern formed by the gas-solid interaction.