Evidence map›Paper›PMID 36235976›Full record

ArticlePolymers2022

Significant Shear Failure Difference among Additively Manufactured Polymers Using Different Techniques.

Luoyu Roy Xu, Qinglin Wang, Yinxu Ni, Gonghe Zhang, Fenghua Liu, Xiaodong Zheng, Yang Liu

Abstract read
In one paragraph

Article in Polymers, 2022. 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
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0citing papers in PubMed
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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

7 authors.

Luoyu Roy XuSchool of Mechanical Engineering and Mechanics, Ningbo University, Ningbo 315211, China.ORCID 0000-0002-9502-7462
Qinglin WangSchool of Mechanical Engineering and Mechanics, Ningbo University, Ningbo 315211, China.
Yinxu NiZhejiang Key Laboratory of Additive Manufacturing Materials, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315211, China.
Gonghe ZhangSchool of Mechanical Engineering and Mechanics, Ningbo University, Ningbo 315211, China.
Fenghua LiuZhejiang Key Laboratory of Additive Manufacturing Materials, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315211, China.
Xiaodong ZhengSchool of Mechanical Engineering and Mechanics, Ningbo University, Ningbo 315211, China.
Yang LiuSchool of Mechanical Engineering and Mechanics, Ningbo University, Ningbo 315211, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Because additively manufactured materials are increasingly being used in load-bearing structures, strength research has become critical. Surprisingly, numerous studies have reported the tensile strength measurements, but only a few studies have presented meaningful results for the shear strength measurements of additively manufactured polymers. Hence, this paper proposes a combined experimental and numerical investigation of a new interlayer shear strength measurement approach, and it targeted the applications of the same polyamide (PA12) specimens made with fused deposition modeling (FDM) and selective laser sintering (SLS). A necking-shaped shear specimen was developed to measure the pure shear strengths with the aid of a three-dimensional (3D) finite element analysis. The results showed that the specimens made with FDM and SLS exhibited totally different shear failure behaviors. The ultimate shear strength of the FDM-PA specimens had more than a 32% increase over that of the SLS-PA specimens. An interface mechanics assumption was employed to explore the different shear failure mechanisms with the support of a fractography analysis.

Indexed as

fused deposition modelingpolymerselective laser sinteringshear strength

Identifiers

PMID36235976
PMCPMC9572911

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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.