Report on in vitro dosimetry model and its applicability for the MOMENTUM MNPs

As part of the MOMENTUM project (see Momentum | Universiteit Utrecht | Homepage (momentummicroplastics.nl)), dosimetry predictions were explored to determine sedimentation of micro and nanoplastics (MNPs) during in vitro experiments (i.e. the fraction of MNP deposited on the cells versus the nominal concentration of NMPs added to the in vitro test system). In the present report, the Distorted Grid model (DG) model was used for the prediction of the sedimentation of a panel of Momentum MNPs due to its enhanced capabilities in handling complex MNP dynamics. Here, the deliverable document is published and made accessible to the public.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-13
DOI
https://doi.org/10.5281/zenodo.15017965
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
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article

Report on in vitro dosimetry model and its applicability for the MOMENTUM MNPs

Zenodo (CERN European Organization for Nuclear Research)
Meteorological Phenomena and Simulations
article

Report on in vitro dosimetry model and its applicability for the MOMENTUM MNPs

article en

Abstract

As part of the MOMENTUM project (see Momentum | Universiteit Utrecht | Homepage (momentummicroplastics.nl)), dosimetry predictions were explored to determine sedimentation of micro and nanoplastics (MNPs) during in vitro experiments (i.e. the fraction of MNP deposited on the cells versus the nominal concentration of NMPs added to the in vitro test system). In the present report, the Distorted Grid model (DG) model was used for the prediction of the sedimentation of a panel of Momentum MNPs due to its enhanced capabilities in handling complex MNP dynamics. Here, the deliverable document is published and made accessible to the public.

Zenodo (CERN European Organization for Nuclear Research)
Utrecht University (NL), Wageningen University & Research (NL)
Openalex Percentile: Top 44%
Meteorological Phenomena and Simulations
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