Analysis of nanomechanical sensing signals; physical parameter estimation for gas identification

Nanomechanical sensors—emerging chemical sensors which detect changes in mechanical properties caused by gas sorption—have been attracting much attention owing to their high sensitivity and versatility. In the data analysis of sensing signals, empirically extracted signal features have been commonly employed to identify the gas species. Such an empiric approach cannot be optimized further without a solid guideline, resulting in a limited identification performance. Therefore, a new analytical protocol based on intrinsic physical properties of a target gas and a receptor material has been highly demanded. In this study, we have developed a parameter estimation protocol based on a theoretical model for a cantilever-type nanomechanical sensor coated with a viscoelastic material. This protocol provides a practical estimation method for intrinsic parameters, which can be used for gas identification. As a demonstration of gas identification based on intrinsic parameters, we focused on the time constant for gas diffusion τs, which reflects the physicochemical interaction between gas species and a receptor material. Based on τs estimated from different receptor materials, we succeeded in the identification of solvent vapors. This parameter estimation protocol not only enables the gas identification based on the intrinsic property of target gases, but also provides a scientific guideline for the selection and optimization of receptor materials for nanomechanical sensors.