Evidence map›Paper›PMID 42213121›Full record

ArticleAnalytical and bioanalytical chemistry2026

Challenges and solutions in the analysis of micro- and nanoplastics down to 500 nm with automated Raman microspectroscopy: suitable filters, accuracy in the detection, identification, and quantification.

Isabel S Jüngling, Lucas Schmitt, Filippo De Franceschi, Paulo A Da Costa Filho, Lei Lei, Laureen Coic, Nizar Benismail, Stephane Dubascoux, Mark E Ambühl, Natalia P Ivleva

Abstract read
In one paragraph

Article in Analytical and bioanalytical chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Isabel S JünglingTUM School of Natural Sciences (NAT, Department Chemistry), Institute of Water Chemistry (IWC), Chair of Analytical Chemistry and Water Chemistry, Technical University of Munich, Lichtenbergstr. 4, 85748, Garching, Germany.ORCID http://orcid.org/0009-0001-6305-5119
Lucas SchmittTUM School of Natural Sciences (NAT, Department Chemistry), Institute of Water Chemistry (IWC), Chair of Analytical Chemistry and Water Chemistry, Technical University of Munich, Lichtenbergstr. 4, 85748, Garching, Germany.
Filippo De FranceschiSociété Des Produits Nestlé S.A. Nestlé Research, Route du Jorat 57, Lausanne, Switzerland.
Paulo A Da Costa FilhoSociété Des Produits Nestlé S.A. Nestlé Research, Route du Jorat 57, Lausanne, Switzerland.
Lei LeiSociété Des Produits Nestlé S.A. Nestlé Research, Route du Jorat 57, Lausanne, Switzerland.
Laureen CoicNestle Quality Assurance Center Vittel, 1020 Avenue Georges Clemenceau, 88800, Vittel, France.
Nizar BenismailNestle Quality Assurance Center Vittel, 1020 Avenue Georges Clemenceau, 88800, Vittel, France.ORCID http://orcid.org/0009-0005-5374-8674
Stephane DubascouxSociété Des Produits Nestlé S.A. Nestlé Research, Route du Jorat 57, Lausanne, Switzerland.
Mark E AmbühlSociété Des Produits Nestlé S.A. Nestlé Research, Route du Jorat 57, Lausanne, Switzerland.ORCID http://orcid.org/0000-0001-5561-3048
Natalia P IvlevaTUM School of Natural Sciences (NAT, Department Chemistry), Institute of Water Chemistry (IWC), Chair of Analytical Chemistry and Water Chemistry, Technical University of Munich, Lichtenbergstr. 4, 85748, Garching, Germany. natalia.ivleva@tum.de.ORCID http://orcid.org/0000-0002-7685-5166

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microplastics (1 µm-5 mm) and nanoplastics (<1 µm) are emerging contaminants with potential health implications, requiring reliable detection for risk assessment. Raman microspectroscopy offers combined morphological and chemical information for identifying micro- and nanoplastics (MNPs). This study assesses the feasibility of automated Raman microspectroscopy for detecting and quantifying MNPs down to 500 nm, focusing on suitable filter materials and device precision. Among six tested filters, silicon filters with 1 µm pores (for particles ≥1 µm) and aluminum-coated polycarbonate filters with 0.4 µm pores (Al-PC, for particles ≥500 nm) performed best. They provided strong particle contrast, low background interference, and high Hit Quality Index (HQI) for submicron particles (polystyrene 500 nm beads, median HQI ≈ 91%), outperforming other filters affected by roughness and spectral interference. Automation using open-source software TUM-ParticleTyper 2 with Random Window Sampling enabled unbiased detection and quantification of MNPs down to 500 nm. Several limitations were noted: illumination settings influenced detected particle number and size recognition, with particles oversized by 0.5 µm ± 0.26 µm; stage precision (~100 nm) affected spectral quality and particle number (<100 particles per window) was critical for achieving >90% correct material identification. Validation with 500 nm polystyrene beads yielded 67 ± 10% recovery relative to theoretical values. Analysis of potable water samples showed predominantly non-plastic particles, with only 0.36 ± 0.13% in the 0.5-10 µm range identified as plastics, 18% of them <1 µm. Further method development, particularly for sample preparation, will be required for broader application to water and food samples. For interest only in particles ≥1 µm, filters with pore size closer 1 µm (e.g., silicon) are recommended. Overall, automated Raman microspectroscopy can quantitatively analyze MNPs down to 500 nm, supporting improved plastic exposure risk assessment.

Indexed as

AutomationFilterMicroplasticsNanoplasticsRaman microspectroscopyWater samples

Identifiers

PMID42213121
PMCPMC13424059

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.