Evidence map›Paper›PMID 33477326›Full record

ArticleToxins2021

Enhanced Photocatalytic Removal of Cyanotoxins by Al-Doped ZnO Nanoparticles with Visible-LED Irradiation.

Majdi Benamara, Elvira Gómez, Ramzi Dhahri, Albert Serrà

Abstract read
In one paragraph

Article in Toxins, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

4 authors.

Majdi BenamaraLaboratory of Physics of Materials and Nanomaterials Applied at Environment (LaPhyMNE), Faculty of Sciences, University of Gabes, Erriadh Manara Zrig, 6072 Gabes, Tunisia.ORCID 0000-0002-0690-8787
Elvira GómezThin Films and Nanostructures Electrodeposition Group (GE-CPN), Department of Materials Science and Physical Chemistry, University of Barcelona, Martí i Franquès 1, E-08028 Barcelona, Spain.ORCID 0000-0002-9223-6357
Ramzi DhahriDepartment of Engineering, University of Messina, 98166 Messina, Italy.
Albert SerràThin Films and Nanostructures Electrodeposition Group (GE-CPN), Department of Materials Science and Physical Chemistry, University of Barcelona, Martí i Franquès 1, E-08028 Barcelona, Spain.ORCID 0000-0003-0147-3400

Funding

Ministerio de Economía, Industria y Competitividad, Gobierno de España TEC2017-85059-C3-2-R
6 · The paper itself

Abstract

The ZnO-based visible-LED photocatalytic degradation and mineralization of two typical cyanotoxins, microcystin-LR (MC-LR), and anatoxin-A were examined. Al-doped ZnO nanoparticle photocatalysts, in Al:Zn ratios between 0 and 5 at.%, were prepared via sol-gel method and exhaustively characterized by X-ray diffraction, transmission electron microscopy, UV-vis diffuse reflectance spectroscopy, photoluminescence spectroscopy, and nitrogen adsorption-desorption isotherms. With both cyanotoxins, increasing the Al content enhances the degradation kinetics, hence the use of nanoparticles with 5 at.% Al content (A5ZO). The dosage affected both cyanotoxins similarly, and the photocatalytic degradation kinetics improved with photocatalyst concentrations between 0.5 and 1.0 g L

Indexed as

Photochemical ProcessesAluminumCatalysisCyanobacteria ToxinsHydrogen-Ion ConcentrationKineticsLightMarine ToxinsMetal NanoparticlesMicrocystinsPhotochemistryPhotolysisTropanesWater Pollutants, ChemicalZinc OxideAluminumanatoxin aCyanobacteria Toxinscyanoginosin LRMarine ToxinsMicrocystinsTropanesWater Pollutants, ChemicalZinc Oxideanatoxin-(a)cyanotoxinsLEDsmicrocystin-LRphotocatalysisvisible lightZnO-doped nanoparticles

Identifiers

PMID33477326
PMCPMC7829790

What OpenQuestion holds

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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.