Complementary Multisplit Ring Resonant MEMS Sensor With Microfilter for Microplastics Concentration Measurement

This article proposes a comprehensive design of the complementary multisplit ring resonant (CMSRR) sensor with microelectromechanical systems (MEMS) microfilter (MMF) that can measure the concentration of microplastics (MPs) simply and intuitively. The proposed sensor estimates the amounts of MPs by injecting a small amount of sample and measuring the notch frequency shift according to the amounts of MPs. In the overall design process of the proposed sensor, the physical dimension of the MMF should be determined based on the size of the measured and accumulated MPs. The CMSRR pattern is configured based on the dimension of the MMF, and the design optimization is performed on the number of split rings, which has the most significant effect on the sensitivity. The proposed sensor was fabricated by bonding the MMF and the CMSRR printed circuit board (PCB) through a thin adhesive. The MMF accumulates the injected MPs through a filter and reservoir structure. When the MPs are injected into the MMF, the notch frequency of the CMSRR sensor shifts with high sensitivity depending on MPs accumulated into the MMF. The sensitivity analysis related to the split patterns was demonstrated through the equivalent circuit model analysis and simulation. To experiment the performance of the proposed sensor, we prepared a polyethylene (PE) dispersion of 1% concentration for each size, 50 and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$80 \mu \text{m}$ </tex-math></inline-formula> . The notch frequency shift of the proposed sensor was measured by the scattering parameter data obtained from a network analyzer. The proposed sensor has 2.84 GHz of intrinsic notch frequency and exhibits a sensitivity that the notch frequency shifts by approximately 14.3 MHz when injected with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5 \mu \text{L}$ </tex-math></inline-formula> of 1% PE dispersion. This article presents the principal component analysis (PCA) based on the experimental measurement results. Through PCA, we visualize the clustering of the entire S21 pattern. Unlike conventional MP measurement methods that use high-cost spectroscopic equipment and can only be performed in a laboratory, the proposed sensor can measure MPs immediately at the site where the sample is taken. In addition, the proposed sensor can collect and measure the MPs of a specific size by filtering them during the measurement process, which was not available in the conventional methods. This advantage results from the sensor’s high mass productivity and low cost, which can be available through fabrication using both an in-house MEMS process and a commercial PCB process. Also, the proposed sensor has a small size with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${28} \times {40} \times {1.4}$ </tex-math></inline-formula> mm3.