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 Sign in to save

Microplastic Detection in Soil and Water Using Resonance Microwave Spectroscopy: A Feasibility Study

IEEE Sensors Journal 2020 61 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Oleksandr Malyuskin

Summary

Researchers conducted a feasibility study using resonance microwave reflectometry to detect and quantify microplastics in soil and water, demonstrating that microplastic concentration could be expressed as a linear function of measured S11 resonance frequency shifts in artificially prepared samples.

A feasibility study of microplastic detection and quantification in soil and water using resonance microwave reflectometry is carried out using artificially created samples with a high volumetric concentration of microplastic with 50 μm-0.5 mm particles size. A mathematical model expressing microplastic concentration in soil and water as a linear function of the measured S 11 resonance frequency shift and relative permittivity contrast is developed and is found to be in an excellent agreement with the experimental data based on synthetic contaminated material samples. Next, this model is applied to find the best achievable theoretical resolution of microplastic concentration in the natural environment using microwave sensing technology, which is shown to be at around 100ppm (parts-per-million) level in the linear signal detection regime. It is demonstrated that the best achievable level of microplastic contaminant resolution depends on the sensor probe Q-factor and sensitivity of the microwave receiver. The bound for the achievable contaminant concentration resolution is found in the analytical form for high-Q resonance microwave sensors of arbitrary geometry. Even though several well-established protocols based on optical, infrared, and X-ray spectroscopy are currently being used for microplastic detection in the natural environment, microwave spectroscopy could offer additional benefits, especially for low-cost, real-time in-situ microplastic detection in diverse environmental conditions outside of the laboratory space.

Sign in to start a discussion.

More Papers Like This

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

Size and concentration characterization of microplastic particles in aqueous samples using sensitivity-enhanced coupled planar microwave resonators

Researchers developed a novel microwave sensing platform for real-time detection and characterization of microplastic particles in water samples. The sensor uses an enhanced coupled planar microwave resonator design with a low-cost disposable sample holder, enabling rapid, non-destructive measurement of microplastic particle size and concentration without cross-contamination between tests.

Article Tier 2

Sub-6 GHz Microwave Sensor Targeting Microplastic Detection

Researchers designed an enhanced sub-6 GHz microwave sensor for low-cost microplastic detection by modifying sensor geometry to better utilize the bandwidth of portable microwave vector network analyzers. Electromagnetic simulations and experimental measurements validated the redesigned sensor, which calibrates resonant frequency as a function of effective permittivity to quantify microplastic concentrations in water.

Article Tier 2

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

Researchers developed a low-cost microwave sensor combined with machine learning to detect and quantify microplastics in water and identify polymer types in unknown samples. The platform achieved the highest sensitivity reported among microwave-based approaches for microplastic detection, offering a promising low-cost alternative to spectroscopy-based methods.

Article Tier 2

Comparative Analysis of Sub-6 GHz Microwave Sensors Suitable for Low-Cost In-Situ Microplastic Detection

This engineering paper compares the performance of several microwave resonator sensor designs for detecting microplastics in water, motivated by the growing availability of low-cost handheld instruments. Laboratory tests showed meaningful differences in sensitivity between sensor geometries, with one design showing the highest relative frequency shift in response to a nylon sample. While purely technical, such sensor development work is an important step toward affordable, portable microplastic monitoring tools that could be deployed in rivers, tap water systems, or food processing facilities.

Share this paper