Design, Modeling and Simulation of a Capacitive Size-Discriminating Particulate Matter Sensor for Personal Air Quality Monitoring

• Published in: IEEE sensors journal 2020-02, Vol.20 (4), p.1971-1979
• Main Authors: Oluwasanya, Pelumi W., Rughoobur, Girish, Occhipinti, Luigi G.
• Format: Article
• Language: English
• Subjects: Aerodynamics; Air monitoring; Air quality; air quality monitoring; Airborne particulates; Atmospheric modeling; Capacitive PM2.5 sensor; Charging; Computational fluid dynamics; Computer simulation; Design parameters; Electric fields; Electrodes; Electrostatics; Embedded systems; Environmental monitoring; Finite element analysis; Finite element method; Fluid dynamics; Inflow; Mathematical model; Monitoring; Outdoor air quality; Parameter identification; particle size discrimination; Particulate emissions; particulate matter detection; Sensitivity; Sensors; Solid modeling; Thermophoresis
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2019.2950775

We applied the well-established thermophoretic effect to air quality monitoring. We developed a novel method for particulate matter distribution analysis in an in-flow capacitive detection device. The proposed Multiphysics model combines fluid dynamics of particulate matter influenced by thermophoresis with electric field variations in the active volume space of a charged coplanar interdigitated electrodes. The model allows to anticipate the effect of thermophoresis in separating particles of PM10 and PM2.5 size ranges into different streams from a single particle-entrained flow and provides an estimated value of sensitivity for capacitive PM detection. The model is described through the Finite Element Method from the main equations to the simulation run using COMSOL Multiphysics and validated by comparing the results with literature. We obtained high sensor sensitivity of up to 0.48 zF/particle as far as 18~\mu \text{m} from coplanar electrode surface using the Computational Fluid Dynamics and Heat Transfer, Electrostatics and Particle tracing modules. We compare results of the simulations for different particle positions, electrode width and inter-electrode spacing, then we use the results to identify optimal design parameters for a novel architecture of a PM detection system with high sensitivity down to PM2.5 single particles and embedded particle size discrimination by using 10~\mu \text{m} electrode width and 1\mu \text{m} inter-electrode spacing.