Evidence map›Paper›PMID 36770108›Full record

ArticleMaterials (Basel, Switzerland)2023

Increasing the Hardness and Corrosion Resistance of the Surface of CP-Ti by Plasma Electrolytic Nitrocarburising and Polishing.

Sergei Kusmanov, Ivan Tambovskiy, Sergey Silkin, Roman Nikiforov, Roman Belov

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 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
–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

5 authors.

Sergei KusmanovDepartment of Chemistry, Institute of Mathematical and Natural Sciences, Kostroma State University, 156005 Kostroma, Russia.ORCID 0000-0002-7156-102X
Ivan TambovskiyDepartment of Chemistry, Institute of Mathematical and Natural Sciences, Kostroma State University, 156005 Kostroma, Russia.
Sergey SilkinDepartment of Chemistry, Institute of Mathematical and Natural Sciences, Kostroma State University, 156005 Kostroma, Russia.
Roman NikiforovDepartment of Chemistry, Institute of Mathematical and Natural Sciences, Kostroma State University, 156005 Kostroma, Russia.ORCID 0000-0002-0685-3739
Roman BelovDepartment of Chemistry, Institute of Mathematical and Natural Sciences, Kostroma State University, 156005 Kostroma, Russia.

Funding

Russian Science Foundation 18-79-10094
6 · The paper itself

Abstract

The possibility of increasing the hardness to 1420 HV and the corrosion resistance of the CP-Ti surface using a combined plasma electrolytic treatment consisting in anodic plasma electrolytic nitrocarburising in a solution of ammonia, acetone and ammonium chloride at 900 °C and subsequent plasma electrolytic polishing is shown. The morphology, surface roughness, phase composition, structure and microhardness of the modified layer were studied. The corrosion characteristics of the treated surface were studied through potentiodynamic tests and electrochemical impedance spectroscopy. It has been shown that an increase in the surface roughness has a negative effect on the corrosion resistance. The proposed plasma electrolytic polishing makes it possible to remove the outer porous oxide layer, providing increased corrosion resistance. The highest reduction in the corrosion current density, by 13 times compared to CP-Ti and by two orders compared to a plasma electrolytic nitrocarburising sample, is achieved after plasma electrolytic polishing in a solution of ammonium fluoride (4%) at 300 V for 3 min.

Indexed as

corrosion resistanceCP-TimicrohardnessnitricarburisingPENCPEPplasma electrolytic treatmentpolishingsurface roughness

Identifiers

PMID36770108
PMCPMC9919307

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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.