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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Koistinen, Arto
University of Eastern Finland
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (4/4 displayed)
- 2023Sorting microplastics from other materials in water samples by ultra-high-definition imagingcitations
- 2021Long-term changes in mandibular bone microchemical quality after radiation therapy and underlying systemic malignancy: A pilot studycitations
- 2021The pursuit of resin-dentin bond durabilitycitations
- 2020Detection of amorphous-amorphous phase separation in small molecular co-amorphous mixtures with SEM-EDS.citations
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article
Sorting microplastics from other materials in water samples by ultra-high-definition imaging
Abstract
<jats:p>In this study a commercial particle analyzer was used to image and help sorting microplastic particles (MPs) dispersed in filtrated and de-aerated tap water. The device provides a relatively easy and fast procedure for obtaining ultra-high-definition imaging, allowing the determination of shape, size, and number of 2D-projections of solid particles. The image analysis revealed clear differences among the studied different MPs originating from the grinding of five common grades of plastic sheets as they affect the image rendering differently, principally due to the light scattering either at the surface or in the volume of the microplastics. The high-quality imaging of the device also allows the discrimination of the microplastics from air bubbles with well-defined spherical shapes as well as to obtain an estimate of the size of MPs in a snapshot. We associate the differences among the shapes of the identified MPs in this study depending on the plastic type with known physical properties, such as brittleness, crystallinity, or softness. Furthermore, as a novel method we exploit a parameter based on the light intensity map from moving particles in cuvette flow to sort MPs from other particles, such as, wood fiber, human hair, and air bubbles. Using the light intensity map, which is related to the plastic-water refractive index ratio, the presence of microplastics in water can be revealed among other particles, but not their specific plastic type.</jats:p>