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A smartphone label-free and automated thermo-analytical method based on image analysis to detect microplastics

The Science of The Total Environment 2024 4 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 55 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Federico Figueredo, Federico Figueredo, Sabina Susmel, Mónica Mosquera-Ortega, Mónica Mosquera-Ortega, Mónica Mosquera-Ortega, Francisco Di Lullo, Francisco Di Lullo, Francisco Di Lullo, Sabina Susmel, Francisco Di Lullo, Federico Schaumburg, Eduardo Cortón Federico Schaumburg, Sabina Susmel, Federico Figueredo, Sabina Susmel, Eduardo Cortón Eduardo Cortón

Summary

Scientists developed a low-cost, smartphone-based method that can identify and count microplastics in environmental samples in under five minutes. The technique works by heating particles and using image analysis to detect which ones melt or change shape, distinguishing plastics from non-plastic particles. The method was successfully tested on soil and sand samples and could serve as a quick, accessible screening tool for microplastic contamination.

Microplastics (MPs) are in some ways the expected product of man-made plastics that are considered as a pollutant ubiquitous in the environment. This is particularly notorious in continental waters, along coastlines, and especially in the North Pacific Gyre, sometimes called the Pacific Garbage Patch. Even now, there is growing concern that MPs can harm wildlife, enter the food chain, and end up in the human body. Therefore, the development of new, simpler and easily automated analytical systems is needed to assess the extent of MPs contamination in the environment. In this work, we present a low-cost analytical method capable of identifying, counting, and sizing MPs and differentiating them from non-plastic particles in less than 5 min after performing image-based analysis during a heating ramp between 25 and 220 °C. Using a smartphone and its camera and a dedicated algorithm, semi-crystalline and amorphous MPs such as polyethylene, polypropylene and polystyrene were efficiently identified by determining whether they melt or change size. The method was tested on spiked soil and sand samples as well as on real samples with successful results. A large number of particles can be analyzed simultaneously using an algorithm that eliminates the need for manual operations. The method is presented to be used as the first necessary step to investigate the level of threat (if any) of this new ubiquitous presence.

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