Evidence map›Paper›PMID 37816748›Full record

ArticleScientific reports2023

Investigation of olive leaf extract as a potential environmentally-friendly corrosion inhibitor for carbon steel.

Sherifa Elhady, Hatice Inan, Mahmoud Shaaban, Irene S Fahim

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
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

0 citing papers in PubMed, 13 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 1 institution in 1 country.

Sherifa ElhadySmart Engineering Systems Centre, Nile University, Cairo, Egypt.
Hatice InanSmart Engineering Systems Centre, Nile University, Cairo, Egypt.
Mahmoud ShaabanSmart Engineering Systems Centre, Nile University, Cairo, Egypt.
Irene S FahimSmart Engineering Systems Centre, Nile University, Cairo, Egypt. isamy@nu.edu.eg.
Nile University · EG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Corrosion constitutes a significant issue in industries that handle metals. Corrosion inhibitors with a low impact on the environment provide a significant economic benefit in various engineering applications. In this work, the effectiveness of olive leaves extract is evaluated as a cost-effective and environmentally-friendly corrosion inhibitor. The corrosion of carbon steel in different concentrations of hydrochloric acid (0.1, 1.0, and 2.0 M) when protected by an aqueous solution of olive leaf extract of concentrations ranging from 10 to 60 ppm is investigated. A green extraction process based upon water extraction is used to ensure minimum impact on the environment. Results show that the corrosion inhibition efficiency increased as the concentration of the olive leaf extract increased. An analysis of variance showed a significant effect of acidic molarity, temperature, and inhibitor concentration on the corrosion rate. A significant statistical model indicates that the inhibitor exhibits higher efficiencies at higher acidic molarity. Results of SEM and EDX also demonstrated that a protective film of the inhibitor on the specimen surface plays a role in corrosion inhibition, suggesting that the inhibitor molecules are adsorbed at the interface between the carbon steel and the acid solution. The study provides an insight on the corrosion mechanism and highlights the potential of olive oil extract as an eco-friendly alternative to traditional corrosion inhibitors.

Identifiers

PMID37816748
PMCPMC10564776
OpenAlexW4387485987

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.