Preconcentrating sensor systems toward indoor low-concentration VOC detection by goal-oriented, sequential, inverse design strategy

Abstract

The techniques capable of accurately and effectively detecting low-concentration volatile organic compounds (VOCs) are promising for environmental contaminant monitoring and non-invasive disease diagnosis. However, low-concentration measurement and selective quantification of multiple components are two major challenges for VOC detection. This work proposes the idea of a sensing system that incorporates preconcentration and multiple sensor arrays to address the two challenges. The design principles and strategies of the sensing system were discussed, as well as the key requirements and challenges of each step of the design process. We further developed a goal-oriented, sequential, inverse design method for an accurate sensing system of indoor VOCs, enabling the realization of high cross-selectivity detection. We also demonstrate the potential and feasibility of the sensing system with a preconcentrator through illustrative examples. The proposed system is expected to be scalable and intermittent, moving it closer to reliable, commercial, and portable near real-time determinations of specific VOC concentrations. It would promote the effectiveness of indoor air quality (IAQ) assessments and interventions.