Evidence map›Paper›PMID 41900751›Full record

ArticleMaterials (Basel, Switzerland)2026

An RSM-Based Investigation on the Process-Performance Correlation and Microstructural Evolution of Friction Stir Welded 7055 Al/2195 Al-Li Dissimilar T-Joints.

Binbin Lin, Yanjie Han, Duquan Zuo, Nannan Wang, Yuanxiu Zhang, Haoran Fu, Chong Gao

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. 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

7 authors.

Binbin LinSichuan Province Engineering Technology Research Center of General Aircraft Maintenance, Civil Aviation Flight University of China, 46 Nanchang Road, Guanghan 618307, China.
Yanjie HanSichuan Province Engineering Technology Research Center of General Aircraft Maintenance, Civil Aviation Flight University of China, 46 Nanchang Road, Guanghan 618307, China.
Duquan ZuoSichuan Province Engineering Technology Research Center of General Aircraft Maintenance, Civil Aviation Flight University of China, 46 Nanchang Road, Guanghan 618307, China.ORCID 0000-0002-5053-0400
Nannan WangLuoyang College, Civil Aviation Flight University of China, Luoyang 471000, China.ORCID 0009-0001-1039-2867
Yuanxiu ZhangSichuan Province Engineering Technology Research Center of General Aircraft Maintenance, Civil Aviation Flight University of China, 46 Nanchang Road, Guanghan 618307, China.
Haoran FuSichuan Province Engineering Technology Research Center of General Aircraft Maintenance, Civil Aviation Flight University of China, 46 Nanchang Road, Guanghan 618307, China.
Chong GaoSchool of Engineering, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan.ORCID 0000-0001-9764-853X

Funding

the Fundamental Research Funds for the Central Universities NO. 24CAFUC07002, and NO. 25CAFUC04018the Sichuan Province Engineering Technology Research Center of General Aircraft Maintenance No. GAMRC2023ZD03the Sichuan Science and Technology Program NO. 2025JDRC0020
6 · The paper itself

Abstract

Friction stir welding (FSW) is a key technology for manufacturing T-shaped thin-walled structures and avoiding fusion welding defects. However, the quantitative relationship between its process parameters and the microstructure properties of the joint remains unclear. To address this, this study established regression models via response surface methodology (RSM) relating rotational speed (

Indexed as

dynamic recrystallizationfriction stir weldingmechanical propertiesmicrostructure evolutionresponse surface methodologyT-joints

Identifiers

PMID41900751
PMCPMC13028133

What OpenQuestion holds

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LicenceCC BY
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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.