Evidence map›Paper›PMID 35739231›Full record

ArticleScientific reports2022

Lead ferrite-activated carbon magnetic composite for efficient removal of phenol from aqueous solutions: synthesis, characterization, and adsorption studies.

Esmaeil Allahkarami, Abolfazl Dehghan Monfared, Luis Felipe Oliveira Silva, Guilherme Luiz Dotto

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Arsenic Oxidation and Removal from Water via Core-Shell MnOInternational journal of environmental research and public health · 2022
    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.

Esmaeil AllahkaramiDepartment of Petroleum Engineering, Faculty of Petroleum, Gas and Petrochemical Engineering, Persian Gulf University, Bushehr, 75169-13817, Iran.
Abolfazl Dehghan MonfaredDepartment of Petroleum Engineering, Faculty of Petroleum, Gas and Petrochemical Engineering, Persian Gulf University, Bushehr, 75169-13817, Iran. dehghan@pgu.ac.ir.
Luis Felipe Oliveira SilvaDepartment of Civil and Environmental, Universidad de La Costa, CUC, Calle 58 # 55-66, Barranquilla, Atlántico, Colombia.
Guilherme Luiz DottoChemical Engineering Department, Federal University of Santa Maria, UFSM, Roraima Avenue 1000, Santa Maria, RS, 97105900, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel lead ferrite-magnetic activated carbon (lead ferrite-MAC) composite was developed using the chemical co-precipitation method. Instrumental analyses such as X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET) analysis were performed to characterize adsorbent. The uptake of phenol from aqueous solutions using the developed adsorbent was compared to that of pristine activated carbon. The maximum adsorption capacity of lead ferrite-MAC composite (145.708 mg/g) was more than that of pristine activated carbon (116.606 mg/g) due to the metal hydroxides coated on activated carbon since they improve the retention of phenol on the available active sites of adsorbent and create an additional electrostatic interaction with the phenol adsorbate. Regarding the high value of the coefficient of determination (R

Indexed as

CharcoalWater Pollutants, ChemicalAdsorptionFerric CompoundsKineticsMagnetic PhenomenaPhenolSpectroscopy, Fourier Transform InfraredWaterCharcoalFerric CompoundsferritePhenolWaterWater Pollutants, Chemical

Identifiers

PMID35739231
PMCPMC9226004

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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.