Evidence map›Paper›PMID 41663698›Full record

ArticleScientific reports2026

Effects of cryogenic cooling on cutting temperature and surface roughness in turning of AA7075 aluminum alloy.

Sadegh Ranjbar, Abolfazl Foorginejad, Sayyed Mohammad Emam, Morvarid Ebadi, Keyvan Shiri

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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.

Sadegh RanjbarDepartment of Mechanical Engineering, Birjand University of Technology, Birjand, Iran.
Abolfazl FoorginejadDepartment of Mechanical Engineering, Birjand University of Technology, Birjand, Iran.
Sayyed Mohammad EmamDepartment of Mechanical Engineering, Faculty of Engineering, Ardakan University, P.O. Box 184, Ardakan, Iran.
Morvarid EbadiDepartment of Biomedical Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran. morvarid_ebadi@yahoo.com.ORCID http://orcid.org/0000-0001-6137-6456
Keyvan ShiriDepartment of Mechanical Engineering, University of Tehran, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The machining process is one of the most widely used methods for converting raw materials into finished products across various industries, owing to its numerous advantages, such as high precision, the capability to produce complex geometries, and superior surface finish. AA7075 aluminum alloy is extensively utilized in the aerospace and automotive sectors due to its exceptional strength-to-weight ratio, moderate corrosion resistance, and fair machinability. During machining operations, the simultaneous imposition of mechanical and thermal loads, coupled with severe plastic deformation, induces changes in the material’s mechanical and metallurgical properties—these alterations must be considered to enhance the component’s performance. Consequently, the surface integrity of the machined part, encompassing metallurgical, mechanical, and topographical aspects, is of paramount importance. Surface roughness, a key indicator of surface texture, directly influences the fatigue life of the component. Employing techniques such as cryogenic cooling with liquid nitrogen can mitigate the temperature in the cutting zone, thereby enhancing surface quality and prolonging component lifespan. In this investigation, the impacts of various dry and cryogenic machining conditions on surface roughness and thermal loads were examined, and the influential parameters were identified.

Indexed as

Dry-Cryogenic machiningSurface qualityTemperature

Identifiers

PMID41663698
PMCPMC12954075

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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.