Evidence map›Paper›PMID 39184834›Full record

ArticleACS nanoscience Au2024

On-the-Fly Monitoring of the Capture and Removal of Nanoplastics with Nanorobots.

Dean I Velikov, Anna Jancik-Prochazkova, Martin Pumera

Abstract read
In one paragraph

Article in ACS nanoscience Au, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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

3 authors.

Dean I VelikovFuture Energy and Innovation Laboratory, Central European Institute of Technology, Brno University of Technology, Purkyňova 123, 612 00 Brno, Czech Republic.ORCID https://orcid.org/0009-0009-9425-0222
Anna Jancik-ProchazkovaFuture Energy and Innovation Laboratory, Central European Institute of Technology, Brno University of Technology, Purkyňova 123, 612 00 Brno, Czech Republic.
Martin PumeraFuture Energy and Innovation Laboratory, Central European Institute of Technology, Brno University of Technology, Purkyňova 123, 612 00 Brno, Czech Republic.ORCID https://orcid.org/0000-0001-5846-2951

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanoplastics are considered an emerging organic persistent pollutant with possible severe long-term implications for the environment and human health; therefore, their remediation is of paramount importance. However, detecting and determining the concentration of nanoparticles in water is challenging and time-consuming due to their small size. In this work, we present a universal yet simple method for the detection and quantification of nanoplastics to monitor their removal from water using magnetic nanorobots. Nanoplastics were stained with a hydrophobic fluorescent dye to enable the use of photoluminescence techniques for their detection and quantification. Magnetic nanorobotic tools were employed to capture and subsequently remove the nanoplastics from contaminated waters. We demonstrated that nanorobots can capture and remove more than 90% of the nanoplastics from an aqueous solution within 120 min. This work shows that easy-to-use common fluorescent dyes combined with photoluminescence spectroscopy methods can be used as an alternative method for the detection and quantification of nanoplastics in water environments and swarming magnetic nanorobots for efficient capture and removal. These methods hold great potential for future research to improve the quantification and removal of nanoplastics in water, and it will ultimately reduce their harmful impact on the environment and human health.

Identifiers

PMID39184834
PMCPMC11342339

What OpenQuestion holds

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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.