0
Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Detection Methods Environmental Sources Policy & Risk Sign in to save

A Fully Integrated Portable Microplastic Detection System-on-Chip With High-Sensitivity RF MEMS Sensors and Narrow-Band Notch-Tracking Dielectric Discrimination Algorithms

IEEE Transactions on Instrumentation and Measurement 2026 Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Seung-Beom Ku, JinHyoung Kim, Kwon-Hong Lee, Han-Sol Lee, Kyeongho Eom, Joonghoon Kang, Hyungjin Jung, Cheolung Cha, Cheolung Cha, Hyungmin Lee

Summary

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.

Study Type Environmental

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.

Sign in to start a discussion.

More Papers Like This

Article Tier 2

Portable Multichannel Measurement System for Real-Time Microplastics Assessment Using Microwave Sensors

Scientists developed a portable multichannel electronic system that uses microwave sensors to detect microplastics in water in real time, capable of simultaneously reading up to four sensors targeting particles of different sizes. The system combines radio-frequency integrated circuits with signal-conditioning hardware for field-deployable monitoring. This kind of low-cost, portable sensing technology could make routine microplastic screening much more practical at waterways and treatment facilities.

Article Tier 2

A Fully Integrated Microplastic Detection SoC with 0.1–3 GHz Bandwidth and 35 dB Dynamic Range for Narrow-Band Notch RF MEMS Sensor System

Engineers developed a miniaturized microwave sensor chip that can detect microplastics in water by measuring shifts in resonant frequency as particles pass through a microfluidic channel, achieving a wide bandwidth and high dynamic range in a compact integrated circuit design. This type of on-chip detection system could enable portable, real-time water quality monitoring for microplastic contamination at a fraction of the cost of laboratory methods.

Article Tier 2

RF MEMS Resonance Sensor for Measuring Microplastics Concentration

Researchers designed an RF MEMS resonance sensor capable of detecting microplastics in water at low cost, offering a practical alternative to expensive conventional particle analyzers for environmental monitoring.

Article Tier 2

An RF MEMS Sensor Driver/Readout SoC With Resonant Frequency Shift and Closed-Loop Envelope Regulation for Portable Microplastic Detection

This paper presents a low-cost portable radio frequency (RF) MEMS sensor system operating at 1.1-1.15 GHz for automated microplastic detection, integrating a driver and readout system-on-chip with resonant frequency shift sensing and closed-loop envelope regulation. The device achieved high-precision microplastic identification, offering a field-deployable alternative to laboratory-based spectroscopic methods.

Article Tier 2

A Microwave-Based Sensing Platform for Microplastic Detection and Quantification: A Machine Learning-Assisted Approach

Researchers developed a low-cost microwave spiral sensor that can detect and differentiate three common types of microplastic (PTFE, PVC, PET) in water, achieving the highest sensitivity reported for microwave-based approaches and using machine learning to identify unknown polymer types. Affordable, reliable detection tools like this are critical for routine environmental monitoring of microplastic contamination in drinking water and waterways.

Share this paper