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Fast compressive Raman micro-spectroscopy to image and classify microplastics from natural marine environment.
Grand, Clément; Scotté, Camille; Prado, Énora; El Rakwe, Maria; Fauvarque, Olivier; Rigneault, Hervé.
Afiliação
  • Grand C; Aix Marseille Univ, CNRS, Centrale Med, Institut Fresnel, Marseille, France.
  • Scotté C; Aix Marseille Univ, CNRS, Centrale Med, Institut Fresnel, Marseille, France.
  • Prado É; INRAE, UMR ITAP, 361 Rue Jean François Breton, Montpellier 34090, France.
  • El Rakwe M; Ifremer, RDT Research and Technological Development, Plouzané 29280, France.
  • Fauvarque O; Ifremer, RDT Research and Technological Development, Plouzané 29280, France.
  • Rigneault H; Ifremer, RDT Research and Technological Development, Plouzané 29280, France.
Environ Technol Innov ; 34: 103622, 2024 May.
Article em En | MEDLINE | ID: mdl-38706940
ABSTRACT
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 mm2 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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Environ Technol Innov Ano de publicação: 2024 Tipo de documento: Article País de afiliação: França

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Environ Technol Innov Ano de publicação: 2024 Tipo de documento: Article País de afiliação: França