研究目的
To develop a miniature system for classification and concentration detection of airborne particulate matter (PM), specifically PM2.5, using a 3D printed virtual impactor and QCM sensor to achieve compactness and portability.
研究成果
The miniature system successfully classifies and detects PM2.5 particles with a cutoff diameter of 2.5 μm, showing linear response to mass loading. It offers advantages in compactness and portability, with potential applications in air pollution monitoring. Future work could enhance sensitivity and integration for broader use.
研究不足
The system may have assembly tolerance issues avoided by 3D printing, but potential limitations include sensitivity to flow rate control, small collection efficiency for larger particles, and deviations in mass concentration measurements (approximately 4% deviation from theoretical values). Optimization could focus on improving accuracy and reducing size further.
1：Experimental Design and Method Selection:
The system integrates a 3D printed virtual impactor for particle size classification and a QCM sensor for mass detection. CFD simulation (using ANSYS 18.0) was used to optimize the virtual impactor design. The Sauerbrey equation is applied for mass sensitivity calculation.
2：0) was used to optimize the virtual impactor design. The Sauerbrey equation is applied for mass sensitivity calculation.
Sample Selection and Data Sources:
2. Sample Selection and Data Sources: Silicon dioxide particles with diameters from 0.5 to 10 μm were generated in a PM chamber using fans.
3：5 to 10 μm were generated in a PM chamber using fans.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: Virtual impactor (3D printed), QCM sensor, micro-pump, network analyzer (Agilent E5061B), fans, photoresist for coating, silicon dioxide particles.
4：Experimental Procedures and Operational Workflow:
Particles are generated and injected into the virtual impactor via a micro-pump. Particles are separated by inertia; small particles (diameter < 2.5 μm) are collected in major flow channels and detected by the QCM sensor. Frequency shifts are measured with a network analyzer.
5：5 μm) are collected in major flow channels and detected by the QCM sensor. Frequency shifts are measured with a network analyzer.
Data Analysis Methods:
5. Data Analysis Methods: Linear fitting of frequency change over time, calculation of mass concentration using the Sauerbrey equation, and comparison with theoretical and simulation results.
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