Evidence map›Paper›PMID 33202720›Full record

ArticleMembranes2020

Reduced Graphene Oxide-Based Foam as an Endocrine Disruptor Adsorbent in Aqueous Solutions.

Jeanne N'Diaye, Sujittra Poorahong, Ons Hmam, Gastón Contreras Jiménez, Ricardo Izquierdo, Mohamed Siaj

Abstract read
In one paragraph

Article in Membranes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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.

Jeanne N'DiayeDepartment of Chemistry and Biochemistry, Université du Québec à Montréal, Montréal, QC H3C 3P8, Canada.ORCID 0000-0002-6031-8833
Sujittra PoorahongDepartment of Chemistry and Biochemistry, Université du Québec à Montréal, Montréal, QC H3C 3P8, Canada.
Ons HmamDepartment of Chemistry and Biochemistry, Université du Québec à Montréal, Montréal, QC H3C 3P8, Canada.
Gastón Contreras JiménezDepartment of Chemistry and Biochemistry, Université du Québec à Montréal, Montréal, QC H3C 3P8, Canada.
Ricardo IzquierdoÉcole de technologie supérieure, Université du Québec à Montréal, Montréal, QC H3C 1K3, Canada.
Mohamed SiajDepartment of Chemistry and Biochemistry, Université du Québec à Montréal, Montréal, QC H3C 3P8, Canada.ORCID 0000-0003-0499-4260

Funding

Canada Research Chairs N/ANatural Sciences and Engineering Research Council of Canada N/A
6 · The paper itself

Abstract

A stable and magnetic graphene oxide (GO) foam-polyethyleneimine-iron nanoparticle (GO-PEI-FeNPs) composite has been fabricated for removal of endocrine disruptors-bisphenol A, progesterone and norethisterone-from aqueous solution. The foam with porous and hierarchical structures was synthesized by reduction of graphene oxide layers coupled with co-precipitation of iron under a hydrothermal system using polyethyleneimine as a cross linker. The presence of magnetic iron nanoparticles facilitates the separation process after decontamination. The foam was fully characterized by surface and structural scanning electron microscopy, Fourier transform infrared spectroscopy, Raman spectroscopy and X-ray photoelectron spectroscopy. The foam exhibits a high adsorption capacity, and the maximum adsorption percentages are 68%, 49% and 80% for bisphenol A, progesterone and norethisterone, respectively. The adsorption process of bisphenol A is explained according to the Langmuir model, whereas the Freundlich model was used for progesterone and norethisterone adsorption.

Indexed as

adsorptionendocrine disruptorsFreundlichLangmuirmembranereduced graphene oxide

Identifiers

PMID33202720
PMCPMC7696572

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.