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