Evidence map›Paper›PMID 38524616›Full record

ArticleHeliyon2024

Synthesis, characterization and application of steel waste-based iron oxide nanoparticles for removal of heavy metals from industrial wastewaters.

Tumutungire Mwebembezi, Joel Wakatuntu, Joseph Jjagwe, Christopher Kanyesigye, Robinah N Kulabako, Peter Wilberforce Olupot

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
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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.

Tumutungire MwebembeziDepartment of Mechanical Engineering, College of Engineering, Design, Art and Technology, Makerere University, P.O. Box 7062, Kampala-Uganda.
Joel WakatuntuDepartment of Mechanical Engineering, College of Engineering, Design, Art and Technology, Makerere University, P.O. Box 7062, Kampala-Uganda.
Joseph JjagweDepartment of Mechanical Engineering, College of Engineering, Design, Art and Technology, Makerere University, P.O. Box 7062, Kampala-Uganda.
Christopher KanyesigyeNational Water and Sewerage Corporation, Plot 3, Nakasero P.O BOX 7053 Kampala, Uganda.
Robinah N KulabakoDepartment of Civil and Environmental Engineering, College of Engineering, Design, Art and Technology, Makerere University, P.O. Box 7062, Kampala-Uganda.
Peter Wilberforce OlupotDepartment of Mechanical Engineering, College of Engineering, Design, Art and Technology, Makerere University, P.O. Box 7062, Kampala-Uganda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Water treatment and reuse can avail more clean and safe water for human use. In this study, iron oxide waste powder generated from the steel pickling process was used to develop iron oxide nanoparticles (IONPs) using solution gelation synthesis process. The powder and developed IONPs were characterized by X-ray fluorescence and diffraction (XRF, XRD), scanning electron microscopy, Fourier-transform infrared spectroscopy, and Brunauer-Emmett-Teller (BET) analyses. Adsorption experiments were carried out on synthetic water with lead and chromium metal ions. The adsorption data were analysed with Langmuir and Freundlich models. Adsorption kinetics were also analysed with Pseudo-First-Order and Pseudo-Second-Order models using non-linear regression. The synthesized IONPs were porous with active surface functional groups of hydroxyl bonds, with BET specific surface area of 325.02 m

Indexed as

Heavy metalsIndustrial wastewater treatmentIron oxide nanoparticlesNanoparticle synthesisSteel pickling waste powder

Identifiers

PMID38524616
PMCPMC10958420

What OpenQuestion holds

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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.