Evidence map›Paper›PMID 42198174›Full record

ArticlePolymers2026

Mechanical Performance of Novel 3D-Printed Symmetric Corrugated Hierarchical Honeycombs.

Derui Zhang, Junpeng Ma, Long Liu, Yan Zhu, Anfu Guo, Peng Qu, Shuai Guo, Zengrui Song, Yaqin Song, Shaoqing Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Polymers, 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. Review
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

10 authors.

Derui ZhangSchool of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng 252000, China.
Junpeng MaSchool of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng 252000, China.
Long LiuShaanxi Special Equipment Inspection and Testing Institute, Xi'an 710048, China.
Yan ZhuSchool of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng 252000, China.
Anfu GuoSchool of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng 252000, China.ORCID 0000-0001-5629-2098
Peng QuSchool of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng 252000, China.
Shuai GuoSchool of Materials Science and Engineering, Liaocheng University, Liaocheng 252000, China.
Zengrui SongSchool of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng 252000, China.
Yaqin SongState Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an 710049, China.ORCID 0000-0002-4729-9148
Shaoqing WangSchool of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng 252000, China.ORCID 0000-0002-8547-5579

Funding

collaborative innovation project for the vice president of science and technology 2024XT14National Natural Science Foundation of China 52405371Shandong Academy of Sciences ZR2023ME154
6 · The paper itself

Abstract

Symmetric corrugated hierarchical honeycombs (SCHHs) are critical lightweight load-bearing structures, featuring distinctive topological architectures and excellent mechanical performance. However, they are prone to local buckling under out-of-plane compression and shear loading, which degrades their overall load-bearing capacity. To address this limitation, this work proposes an innovative dual-optimization strategy integrating cylindrical support structure introduction and nano-silica (SiO

Indexed as

compressive propertiesenergy absorptionfinite element analysisfriction coefficienthierarchical honeycombs

Identifiers

PMID42198174
PMCPMC13210859

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.