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TUM-ParticleTyper 2: automated quantitative analysis of (microplastic) particles and fibers down to 1 [Formula: see text] m by Raman microspectroscopy

Accurate quantification of small microplastics in environmental and food samples is a prerequisite for studying their potential hazard. Knowledge of numbers, size distributions and polymer type for particles and fibers is particularly relevant in this respect. Raman microspectroscopy can identify pa...

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Autores principales: Jacob, Oliver, Ramírez-Piñero, Alejandro, Elsner, Martin, Ivleva, Natalia P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284940/
https://www.ncbi.nlm.nih.gov/pubmed/37286906
http://dx.doi.org/10.1007/s00216-023-04712-9
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author Jacob, Oliver
Ramírez-Piñero, Alejandro
Elsner, Martin
Ivleva, Natalia P.
author_facet Jacob, Oliver
Ramírez-Piñero, Alejandro
Elsner, Martin
Ivleva, Natalia P.
author_sort Jacob, Oliver
collection PubMed
description Accurate quantification of small microplastics in environmental and food samples is a prerequisite for studying their potential hazard. Knowledge of numbers, size distributions and polymer type for particles and fibers is particularly relevant in this respect. Raman microspectroscopy can identify particles down to 1 [Formula: see text] m in diameter. Here, a fully automated procedure for quantifying microplastics across the entire defined size range is presented as the core of the new software TUM-ParticleTyper 2. This software implements the theoretical approaches of random window sampling and on-the-fly confidence interval estimation during ongoing measurements. It also includes improvements to image processing and fiber recognition (when compared to the previous software TUM-ParticleTyper for analysis of particles/fibers [Formula: see text]  [Formula: see text] m), and a new approach to adaptive de-agglomeration. Repeated measurements of internally produced secondary reference microplastics were evaluated to assess the precision of the whole procedure. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00216-023-04712-9.
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spelling pubmed-102849402023-06-23 TUM-ParticleTyper 2: automated quantitative analysis of (microplastic) particles and fibers down to 1 [Formula: see text] m by Raman microspectroscopy Jacob, Oliver Ramírez-Piñero, Alejandro Elsner, Martin Ivleva, Natalia P. Anal Bioanal Chem Research Paper Accurate quantification of small microplastics in environmental and food samples is a prerequisite for studying their potential hazard. Knowledge of numbers, size distributions and polymer type for particles and fibers is particularly relevant in this respect. Raman microspectroscopy can identify particles down to 1 [Formula: see text] m in diameter. Here, a fully automated procedure for quantifying microplastics across the entire defined size range is presented as the core of the new software TUM-ParticleTyper 2. This software implements the theoretical approaches of random window sampling and on-the-fly confidence interval estimation during ongoing measurements. It also includes improvements to image processing and fiber recognition (when compared to the previous software TUM-ParticleTyper for analysis of particles/fibers [Formula: see text]  [Formula: see text] m), and a new approach to adaptive de-agglomeration. Repeated measurements of internally produced secondary reference microplastics were evaluated to assess the precision of the whole procedure. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00216-023-04712-9. Springer Berlin Heidelberg 2023-06-08 2023 /pmc/articles/PMC10284940/ /pubmed/37286906 http://dx.doi.org/10.1007/s00216-023-04712-9 Text en © The Author(s) 2023, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Paper
Jacob, Oliver
Ramírez-Piñero, Alejandro
Elsner, Martin
Ivleva, Natalia P.
TUM-ParticleTyper 2: automated quantitative analysis of (microplastic) particles and fibers down to 1 [Formula: see text] m by Raman microspectroscopy
title TUM-ParticleTyper 2: automated quantitative analysis of (microplastic) particles and fibers down to 1 [Formula: see text] m by Raman microspectroscopy
title_full TUM-ParticleTyper 2: automated quantitative analysis of (microplastic) particles and fibers down to 1 [Formula: see text] m by Raman microspectroscopy
title_fullStr TUM-ParticleTyper 2: automated quantitative analysis of (microplastic) particles and fibers down to 1 [Formula: see text] m by Raman microspectroscopy
title_full_unstemmed TUM-ParticleTyper 2: automated quantitative analysis of (microplastic) particles and fibers down to 1 [Formula: see text] m by Raman microspectroscopy
title_short TUM-ParticleTyper 2: automated quantitative analysis of (microplastic) particles and fibers down to 1 [Formula: see text] m by Raman microspectroscopy
title_sort tum-particletyper 2: automated quantitative analysis of (microplastic) particles and fibers down to 1 [formula: see text] m by raman microspectroscopy
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284940/
https://www.ncbi.nlm.nih.gov/pubmed/37286906
http://dx.doi.org/10.1007/s00216-023-04712-9
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