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A Fully Integrated Portable Microplastic Detection System-on-Chip With High-Sensitivity RF MEMS Sensors and Narrow-Band Notch-Tracking Dielectric Discrimination Algorithms
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Researchers developed a compact, portable chip that can detect and identify common microplastic types (PE, PP, PET, PS, PMMA) using radio-frequency sensors and signal-tracking algorithms, validating results against real-world samples including laundry wastewater. This kind of low-cost, on-site detection technology is important because existing lab-based methods are expensive and slow, limiting how widely microplastics can be monitored in the environment.
This article presents a fully integrated portable microplastic (MP) detection system-on-chip (SoC) that combines high-sensitivity radio frequency (RF) micro electromechanical systems (MEMS) sensors with narrow-band notch-tracking algorithms for dielectric discrimination. Conventional MP detection systems suffer from the low transmit power (PTX), restricted receiver dynamic range (DR), and the need for separate two-chip configurations, increasing complexity and cost. To overcome these challenges, the proposed 180-nm CMOS MP detection SoC monolithically integrates the sensor driver and readout functionalities, eliminating the need for multiple chips and reducing power consumption. The MP detection SoC, originally developed for a 1.2 GHz notch RF MEMS sensor, was also evaluated with a 2.84 GHz sensor, demonstrating its scalability for high-frequency MP detection. The system tracks the resonance points of the RF MEMS sensor to monitor transmission coefficient (S21) variations, enabling quantitative analysis of MPs such as polyethylene (PE), polypropylene (PP), polyethylene terephthalate (PET), polystyrene (PS), and polymethyl methacrylate (PMMA). By correlating notch frequency shifts with variations in relative permittivity (εr) and loss tangent [tan(δ)], it performs stepwise MP detection and enables quantitative analysis of MPs. The system was validated using real-world MPs, including 3D printer filament (PLA), aged water pipelines, and laundry wastewater, showing results consistent with thermogravimetric analysis-Fourier transform-infrared (TGA-FT-IR) spectroscopy, with error rates ranging from 10% to 23%. These results highlight a compact, portable, and reliable solution for on-site MP detection under realistic environmental conditions.
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