Evidence map›Paper›PMID 37374553›Full record

ArticleMaterials (Basel, Switzerland)2023

Effect of Artificial Aging Treatment on the Mechanical Properties and Regulation of Precipitated Phase Particles of High-Pressure Die-Cast Thin-Wall AlSi10MnMg Longitudinal Carrier.

Xu Zhao, Ping Wang, Yang Yang, Song Wang, Qiang Zhao, Jingying Sun

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 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

6 authors.

Xu ZhaoKey Laboratory of Electromagnetic Processing of Materials, Ministry of Education, Northeastern University, Shenyang 110819, China.
Ping WangKey Laboratory of Electromagnetic Processing of Materials, Ministry of Education, Northeastern University, Shenyang 110819, China.
Yang YangBMW-Brilliance Automotive Ltd., Shenyang 100044, China.
Song WangBMW-Brilliance Automotive Ltd., Shenyang 100044, China.
Qiang ZhaoBMW-Brilliance Automotive Ltd., Shenyang 100044, China.
Jingying SunShenyang Wesszin Technology Co., Ltd., Shenyang 110044, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates the artificial aging treatment process for AlSi10MnMg longitudinal carriers with optimal strength and ductility. Experimental results illustrate that the peak strength is observed under single-stage aging at 180 °C × 3 h, with a tensile strength of 332.5 MPa, Brinell hardness of 133.0 HB, and elongation of 5.56%. As aging time increases, tensile strength and hardness initially increase and then decrease, while elongation displays an inverse pattern. The amount of secondary phase particles at grain boundaries increases with aging temperature and holding time, but stabilizes as aging progresses; the secondary phase particles begin to grow, eventually weakening the alloy's strengthening effect. The fracture surface exhibits mixed fracture characteristics, including ductile dimples and brittle cleavage steps. Range analysis indicates that the influence of distinct parameters on mechanical properties post-double-stage aging is as follows: first-stage aging time, first-stage aging temperature, followed again by second-stage aging time, and second-stage aging temperature. For peak strength, the optimal double-stage aging process includes a first-stage aging temperature of 100 °C × 3 h and a second-stage aging temperature of 180 °C × 3 h.

Indexed as

AlSi10MnMg alloydouble-stage agingmechanical propertiesmicrostructuresingle-stage aging

Identifiers

PMID37374553
PMCPMC10305174

What OpenQuestion holds

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LicenceCC BY
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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.