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 Sign in to save

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

2025 Score: 38 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Mateus I. O. Souza, Leonardo Tarczewski, Leonardo Tarczewski, Bernd Lahr, Achiles F. da Mota, Andrei Leitão, Vinícius M. Pepino, Ben‐Hur V. Borges

Summary

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.

This work introduces a low-cost microwave (MW) sensor that achieves the highest sensitivity among MW-based approaches for detecting microplastics (MPs) in water and provides a mechanism for determining polymer types in unknown samples. These achieveme

Sign in to start a discussion.

More Papers Like This

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.

Article Tier 2

Microfluidic Microwave Sensor for Rapid Detection of Microplastics in Water: Optimization, Modeling, and Performance Evaluation

Researchers developed a microfluidic sensor that uses microwave technology to rapidly detect microplastics in water samples without physical contact. The sensor was optimized to distinguish between different concentrations and sizes of plastic particles with high sensitivity. The technology could enable faster and more practical on-site monitoring of microplastic contamination in water supplies.

Article Tier 2

Detection of microplastics by microfluidic microwave sensing: An exploratory study

Researchers developed a compact microwave sensor on a microfluidic chip to detect microplastics in water samples. The system works by measuring how the presence of plastic particles changes the electrical properties of water. While the technology shows promise as a rapid and portable detection method, its current sensitivity needs improvement before it can detect the low microplastic concentrations typically found in natural freshwater.

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

Microplastics Detection with Microfluidic Near-Field Microwave Sensors

A new microfluidic sensor integrating a microwave detector was developed that can identify microplastics in water in real time without labelling, by measuring how particles change the dielectric properties of the water flowing through the device. This kind of low-cost, continuous-monitoring sensor could make routine environmental surveillance for microplastic contamination more practical.

Share this paper