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Raman Tweezers for Small Microplastics and Nanoplastics Identification in Seawater
Open accessAbstract
Our understanding of the fate and distribution of micro- and nano- plastics in the marine environment is limited by the intrinsic difficulties of the techniques currently used for the detection, quantification, and chemical identification of small particles in liquid (light scattering, vibrational spectroscopies, and optical and electron microscopies). Here we introduce Raman Tweezers (RTs), namely optical tweezers combined with Raman spectroscopy, as an analytical tool for the study of micro- and nanoplastics in seawater. We show optical trapping and chemical identification of sub-20 μm plastics, down to the 50 nm range. Analysis at the single particle level allows us to unambiguously discriminate plastics from organic matter and mineral sediments, overcoming the capacities of standard Raman spectroscopy in liquid, intrinsically limited to ensemble measurements. Being a microscopy technique, RTs also permits one to assess the size and shapes of particles (beads, fragments, and fibers), with spatial resolution only limited by diffraction. Applications are shown on both model particles and naturally aged environmental samples, made of common plastic pollutants, including polyethylene, polypropylene, nylon, and polystyrene, also in the presence of a thin eco-corona. Coupled to suitable extraction and concentration protocols, RTs have the potential to strongly impact future research on micro and nanoplastics environmental pollution, and enable the understanding of the fragmentation processes on a multiscale level of aged polymers.
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Metadata
- Authors
- Gillibert, R., Balakrishnan, G., Deshoules, Q., Tardivel, M., Magazzù, A., Donato, M. G., Maragò, O. M., Lamy de La Chapelle, M., Colas, F., Lagarde, F., & Gucciardi, P. G.
- Venue
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Published
- 2019-07-01
- Volume
- 53
- Issue
- 15
- Pages
- 9003-9013
- ISSN
- 0013-936X (ISSN-L)
- 1520-5851
- OpenAlex
- W2955409949
- Cited by
- 348
- References
- 90
- FWCI
- 9.42
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.