Evidence map›Paper›PMID 34576605›Full record

ArticleMaterials (Basel, Switzerland)2021

Modeling Bioinspired Fish Scale Designs via a Geometric and Numerical Approach.

Ailin Chen, Komal Thind, Kahraman G Demir, Grace X Gu

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2021. 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. Mechanics of Bio-Inspired Protective Scales.Biomimetics (Basel, Switzerland) · 2025
    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

4 authors.

Ailin ChenDepartment of Mechanical Engineering, University of California, Berkeley, CA 94720, USA.ORCID 0000-0002-7910-0826
Komal ThindDepartment of Mechanical Engineering, University of California, Berkeley, CA 94720, USA.
Kahraman G DemirDepartment of Mechanical Engineering, University of California, Berkeley, CA 94720, USA.
Grace X GuDepartment of Mechanical Engineering, University of California, Berkeley, CA 94720, USA.

Funding

3M 3M Non-Tenured Faculty AwardMcNair Scholars Program N/AOffice of Naval Research N00014-21-1-2604
6 · The paper itself

Abstract

Fish scales serve as a natural dermal armor with remarkable flexibility and puncture resistance. Through studying fish scales, researchers can replicate these properties and tune them by adjusting their design parameters to create biomimetic scales. Overlapping scales, as seen in elasmoid scales, can lead to complex interactions between each scale. These interactions are able to maintain the stiffness of the fish's structure with improved flexibility. Hence, it is important to understand these interactions in order to design biomimetic fish scales. Modeling the flexibility of fish scales, when subject to shear loading across a substrate, requires accounting for nonlinear relations. Current studies focus on characterizing these kinematic linear and nonlinear regions but fall short in modeling the kinematic phase shift. Here, we propose an approach that will predict when the linear-to-nonlinear transition will occur, allowing for more control of the overall behavior of the fish scale structure. Using a geometric analysis of the interacting scales, we can model the flexibility at the transition point where the scales start to engage in a nonlinear manner. The validity of these geometric predictions is investigated through finite element analysis. This investigation will allow for efficient optimization of scale-like designs and can be applied to various applications.

Indexed as

bioinspired designsdermal armorfinite element analysisfish scalesflexible composites

Identifiers

PMID34576605
PMCPMC8467489

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.