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arXiv Machine Learning By Jaden Tolbert, Md Saiful Islam, Pingshan Wang

Radio Frequency Detection and Classification of Microplastics in Water

Read the original on arXiv Machine Learning →

The study introduces a machine learning–assisted radio‑frequency dielectric spectroscopic cytometry platform for detecting and classifying micro‑plastic particles in water. Eight types of 10 µm nominal‑diameter micro‑plastics were distinguished in deionized water using RF scattering parameters measured at 0.2–9 GHz, achieving macro‑average F1‑scores, precision, and recall above 0.71. The method also maintained PET classification performance in saline media up to 6.6 % sea salt, demonstrating feasibility for rapid, single‑particle micro‑plastic identification in aqueous environments.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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