Abstract
This paper reports a micro aerosol sensor for PM1 concentration detection based on three-dimensional (3D) printing virtual impactor (VI) and surface acoustic wave (SAW) sensor. The VI structure has been optimized by computational fluid dynamics (CFD) simulation to realize flow distribution for classifying particles. And when the air flow distribution ratio between the major flow and minor flow is 9:1, the VI presents a good classification performance. The performance of the aerosol sensor is characterized through classification and detection of silicon oxide particles with diameter ranging from 0.1 to $4 \mu \mathrm{m}$ . The results show that particles smaller than $1 \mu \mathrm{m}$ are successfully classified by the VI and the resonant frequency of the SAW sensor decreases linearly with the particles mass increment.
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