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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 Marine & Wildlife Sign in to save

Fast compressive Raman micro-spectroscopy to image and classify microplastics from natural marine environment

Environmental Technology & Innovation 2024 8 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Clément Grand, Camille Scotté, Énora Prado, Maria El Rakwe, Maria El Rakwe, Olivier Fauvarque, Hervé Rigneault

Summary

Researchers developed a fast compressive Raman micro-spectroscopy system for imaging and classifying microplastics on filters, achieving significant speed improvements over conventional point-scanning Raman methods. The system correctly identified polymer types in heterogeneous real-world samples, offering a practical tool for routine microplastic monitoring in water and sediment samples.

The fast and reliable detection of micron-sized plastic particles from the natural marine environment is an important topic that is mostly addressed using spontaneous Raman spectroscopy. Due to the long (>tens of ms) integration time required to record a viable Raman signal, measurements are limited to a single point per microplastic particle or require very long acquisition times (up to tens of hours). In this work, we develop, validate, and demonstrate a compressive Raman technology using binary spectral filters and single-pixel detection that can image and classify six types of marine microplastic particles over an area of 1 mm with a pixel dwell time down to 1.75 ms/pixel and a spatial resolution of 1 µm. This is x10-100 faster than reported in previous studies.

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