Evidence map›Paper›PMID 42852288›Full record

ArticleACS omega2026

Improving the Corrosion Resistance of Steel Alloys Using Polyaniline/Graphene Nanocomposite Coatings.

Hiba A Abdullah, Ali A Muhsan, Saja A Abdul Maged

Abstract read
In one paragraph

Article in ACS omega, 2026. 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
–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

0 citing papers in PubMed.

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

3 authors.

Hiba A AbdullahCollege of Materials Engineering, University of Technology-Iraq, Baghdad 10066, Iraq.
Ali A MuhsanCollege of Materials Engineering, University of Technology-Iraq, Baghdad 10066, Iraq.ORCID https://orcid.org/0000-0002-6987-860X
Saja A Abdul MagedCollege of Materials Engineering, University of Technology-Iraq, Baghdad 10066, Iraq.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work, a polyaniline (PANI)/graphene nanocomposite coating was applied to steel (St 37-2) alloy to enhance its physicochemical properties. The nanocomposite coating consisted of polyaniline and graphene with different weight percentages (1, 5, and 8 wt %). An electrophoretic deposition technique was utilized to apply the nanocomposite coating to the steel alloy, followed by characterization with X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR). XRD patterns indicated the crystal structures for uncoated and coated samples. XRD patterns indicate the crystallinity of the nanocomposite coating due to the appearance of phases related to PANI and graphene. AFM images of the prepared graphene indicate a wrinkled structure, with a graphene sheet thickness of 46.9 nm. SEM images show a uniform and homogeneous nanocomposite coating of PANI/graphene on the steel alloy. FTIR spectra for PANI and graphene indicated the characteristic functional groups. On the other side, the FTIR spectra for the coated samples showed the same spectrum for different weight % of graphene. Corrosion behavior of the steel alloy and coated samples was studied via potentiodynamic polarization at different temperatures. Nanocomposite coating of PANI/graphene enhanced the corrosion resistance of the steel alloy by reducing the corrosion current density for the coated samples because of the uniform and dense coating layer. Also, the protection efficiency improved for the coated samples (80%-90%), which indicates the effectiveness of the nanocomposite coating in decreasing the corrosion of the coated samples.

Indexed as

electrophoretic depositiongraphenenanocomposite coatingpolyanilinesteel alloy

Identifiers

PMID42852288
PMCPMC13647867

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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.