Evidence map›Paper›PMID 34501100›Full record

ArticleMaterials (Basel, Switzerland)2021

Performance Evaluation of Ultra-Violet Light and Iron Oxide Nanoparticles for the Treatment of Synthetic Petroleum Wastewater: Kinetics of COD Removal.

Cecilia O Akintayo, Omolola H Aremu, Wilfred N Igboama, Simphiwe M Nelana, Olushola S Ayanda

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2021. 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

5 authors.

Cecilia O AkintayoNanoscience Research Unit, Department of Industrial Chemistry, Federal University Oye Ekiti, P.M.B 373, Oye Ekiti 362001, Nigeria.
Omolola H AremuNanoscience Research Unit, Department of Industrial Chemistry, Federal University Oye Ekiti, P.M.B 373, Oye Ekiti 362001, Nigeria.
Wilfred N IgboamaDepartment of Physics, Federal University Oye Ekiti, P.M.B 373, Oye Ekiti 362001, Nigeria.
Simphiwe M NelanaDepartment of Chemistry, Vaal University of Technology, Vanderbijlpark 1900, South Africa.
Olushola S AyandaNanoscience Research Unit, Department of Industrial Chemistry, Federal University Oye Ekiti, P.M.B 373, Oye Ekiti 362001, Nigeria.

Funding

Tertiary Education Trust Fund TETFUND/DESS/UNI/OYE-EKITI/2017/RP/VOL.1/5
6 · The paper itself

Abstract

In this study, the use of ultra-violet (UV) light with or without iron oxide nanoparticles (IONPs) for the degradation of synthetic petroleum wastewater was investigated. The IONPs was synthesised by sodium borohydride reduction of ferric chloride solution and was characterised by scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier transform infrared spectrometry (FTIR), x-ray fluorescence spectrophotometry (XRF), and energy dispersive spectroscopy (EDS). The amount of degradation was evaluated by chemical oxygen demand (COD) determination. Experimental results show that the COD removal from synthetic petroleum wastewater by IONPs/UV system was more effective than they were independently. The combination of UV light at a wavelength of 254 nm, pH of 8, and 1.0 g of IONPs resulted in COD removal from 10.5% up to 95.5%. The photocatalytic degradation of synthetic petroleum wastewater is about 1.3-2.0 times faster in comparison to UV light only. The removal of COD from synthetic petroleum wastewater by UV light and IONPs follows the pseudo-first-order kinetic model with rate constant

Indexed as

chemical oxygen demandiron oxide nanoparticlesphotocatalysisrefinery wastewaterultra-violet light

Identifiers

PMID34501100
PMCPMC8434562

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.