Evidence map›Paper›PMID 37469505›Full record

ArticleACS applied nano materials2023

Boron Nitride Nanosheets Functionalized with Fe

Garret Dee, Olivia O'Donoghue, Aran Rafferty, Lee Gannon, Cormac McGuinness, Yurii K Gun'ko

Abstract read
In one paragraph

Article in ACS applied nano materials, 2023. 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

6 authors.

Garret DeeSchool of Chemistry, University of Dublin, Trinity College, Dublin Dublin 2, Ireland.ORCID https://orcid.org/0000-0003-3764-6967
Olivia O'DonoghueSchool of Chemistry, University of Dublin, Trinity College, Dublin Dublin 2, Ireland.
Aran RaffertySchool of Chemistry, University of Dublin, Trinity College, Dublin Dublin 2, Ireland.ORCID https://orcid.org/0000-0001-6388-7735
Lee GannonSchool of Physics University of Dublin, Trinity College, Dublin Dublin 2, Ireland.
Cormac McGuinnessSchool of Physics University of Dublin, Trinity College, Dublin Dublin 2, Ireland.
Yurii K Gun'koSchool of Chemistry, University of Dublin, Trinity College, Dublin Dublin 2, Ireland.ORCID https://orcid.org/0000-0002-4772-778X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanofiltration (NF) is one of the emerging technologies that is very promising for water purification among many other applications. 2D boron nitride (BN) based nanomaterials are excellent building blocks for NF membranes. In our work, BN nanosheets (BNNS) have been functionalized with magnetic nanoparticles (MNPs) to form BNNS-MNP nanocomposites. It was found that the nanocomposites are stable with the MNPs giving very good coverage with both magnetite and cobalt ferrite MNPs and showing good attachment and stability to sonication. These nanocomposites have been tested for removal of methylene blue (MB) dye and MNPs from water. BNNS-magnetite nanocomposites showed higher removal efficiency of the MB from water than the corresponding pure BNNS, while the BNNS-cobalt ferrite removal efficiency was slightly less than the pure BNNS. The BNNS-cobalt ferrite material was regenerated by burning off the MB and recycled to show the recyclability of this material. The BNNS membranes were tested for filtration of 14 ± 4 nm magnetite MNPs and were found to capture 100% of the nanoparticles with no MNPs left in the filtrate. Thus, we have developed magnetic nanocomposite membranes, which have demonstrated great potential for water remediation. We believe that this research opens up promising ways for production of 2D nanocomposite materials with multiple applications.

Identifiers

PMID37469505
PMCPMC10352960

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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.