Evidence map›Paper›PMID 42795228›Full record

ArticleMaterials (Basel, Switzerland)2026

Comparative Study of Microstructure, Phase Composition, Hardness, and Tribological Behavior of Low-Carbon Steel After Electrolytic-Plasma and Laser Surface Hardening.

Laila Sulyubayeva, Dastan Buitkenov, Almasbek Maulit, Balym Alibekova, Sanzhar Bolatov

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 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

5 authors.

Laila SulyubayevaResearch Center Surface Engineering and Tribology, Sarsen Amanzholov East Kazakhstan University, Ust-Kamenogorsk 070000, Kazakhstan.ORCID 0000-0002-1924-1459
Dastan BuitkenovResearch Center Surface Engineering and Tribology, Sarsen Amanzholov East Kazakhstan University, Ust-Kamenogorsk 070000, Kazakhstan.ORCID 0000-0002-0239-5849
Almasbek MaulitPlasmaScience LLP, Oskemen 070018, Kazakhstan.ORCID 0000-0002-0519-3222
Balym AlibekovaResearch Center Surface Engineering and Tribology, Sarsen Amanzholov East Kazakhstan University, Ust-Kamenogorsk 070000, Kazakhstan.ORCID 0009-0001-7644-4527
Sanzhar BolatovResearch Center Surface Engineering and Tribology, Sarsen Amanzholov East Kazakhstan University, Ust-Kamenogorsk 070000, Kazakhstan.ORCID 0009-0003-3136-0535

Funding

the Science Committee of the Ministry of Science and Higher Education of the Republic of Ka-zakhstan ВR24992879
6 · The paper itself

Abstract

The aim of this study was to comparatively evaluate the effects of electrolytic-plasma surface hardening (EPSH) and laser surface hardening (LSH) on the microstructure, phase state, microhardness, and friction behavior of low-carbon Steel 20. EPSH was performed using a two-stage regime of 320 V for 3 s followed by 200 V for 40 s and a thermocyclic regime of 320 V for 2 s, 200 V for 2 s, and 50 V for 2 s repeated for five cycles. LSH was carried out at a scanning speed of 7 mm/s and 75% of the maximum laser power (approximately 2250 W) using single- and double-pass treatments. The modified layers were characterized by SEM, XRD, microhardness measurements, and dry sliding tribological tests. EPSH produced the strongest hardening response, reaching approximately 600 HV with a hardened-layer depth of 70-100 μm. Double-pass LSH increased the near-surface microhardness to approximately 460 HV. Phase analysis revealed Fe

Indexed as

electrolytic-plasma hardeningiron oxideslaser hardeningphase compositionsurface hardeningwear resistanceα′-martensite

Identifiers

PMID42795228
PMCPMC13608533

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.