Evidence map›Paper›PMID 36412704›Full record

ArticleBiomimetics (Basel, Switzerland)2022

Bending Study of Six Biological Models for Design of High Strength and Tough Structures.

Guangming Chen, Tao Lin, Ce Guo, Lutz Richter, Ning Dai

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Guangming ChenCollege of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Tao LinCollege of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.ORCID 0000-0003-3282-8147
Ce GuoCollege of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Lutz RichterLarge Space Structures GmbH, Hauptstr. 1e, D-85386 Eching, Germany.
Ning DaiCollege of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.

Funding

Foundation Research Project of Jiangsu Province Natural Science Fund No. BK20190415International Cooperation Fund for Foreign Experts Working in NUAA G2021181006LNational Natural Science Foundation of China No. 51875282
6 · The paper itself

Abstract

High strength and tough structures are beneficial to increasing engineering components service span. Nonetheless, improving structure strength and, simultaneously, toughness is difficult, since these two properties are generally mutually exclusive. Biological organisms exhibit both excellent strength and toughness. Using bionic structures from these biological organisms can be solutions for improving these properties of engineering components. To effectively apply biological models to design biomimetic structures, this paper analyses strengthening and toughening mechanisms of six fundamentally biological models obtained from biological organisms. Numerical models of three-point bending test are established to predict crack propagation behaviors of the six biological models. Furthermore, the strength and toughness of six biomimetic composites are experimentally evaluated. It is identified that the helical model possesses the highest toughness and satisfying strength. This work provides more detailed evidence for engineers to designate bionic models to the design of biomimetic composites with high strength and toughness.

Indexed as

biomimetic compositescrack propagationfinite element methodthree-point bending test

Identifiers

PMID36412704
PMCPMC9680280

What OpenQuestion holds

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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.