Evidence map›Paper›PMID 37629965›Full record

ArticleMaterials (Basel, Switzerland)2023

Surface Treatments for Enhancing the Bonding Strength of Aluminum Alloy Joints.

Juncheng Luo, Jianhua Liu, Huanxiong Xia, Xiaohui Ao, Haojie Yin, Lei Guo

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. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

6 authors.

Juncheng LuoSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Jianhua LiuSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Huanxiong XiaSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China.ORCID 0000-0001-7106-0658
Xiaohui AoSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Haojie YinSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Lei GuoAir Force Medical Center, PLA, Beijing 100142, China.

Funding

Foundation Enhancement Program No. 2022-JCJQ-JJ-0102Major Fundamental Research of Equipment No. 514010208-301National Fundamental Scientific Research No. JCKY2022203B006National Key Research and Development Program of China No. 2022YFB3403801
6 · The paper itself

Abstract

Aluminum alloy adhesive bonding joint widely appears in many industrial products. Improving the mechanical performances of aluminum alloy bonding joints has been attracting much effort. To acquire more excellent bonding strength, this paper focused on the effects of different surface treatments, including laser ablation and milling superposed by phosphoric acid anodizing (PAA). The treated surfaces were characterized by roughness and contact angle, and the effects of the geometric parameters of microstructures on wettability, failure mode, and shear strength were examined. The results indicate that those surfaces where the spacing is smaller than the diameter present a hydrophilic property and the corresponding specimens are mainly subject to cohesive failure, and vice versa. Additionally, laser ablation with a properly designed dimple pattern can greatly improve the bonding strength, and the maximum average shear strength of specimens with a thickness of 50 μm reaches 32.82 MPa, which is an increase of 28.15% compared with the original milling specimen. Moreover, fabricating groove or grid patterns on the surfaces and applying PAA treatment can also significantly enhance the bonding strength, reaching up to 36.28 MPa.

Indexed as

bonding strengthlaser ablationmicrostructurephosphoric acid anodizingsurface treatment

Identifiers

PMID37629965
PMCPMC10456362

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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.