Evidence map›Paper›PMID 42041507›Full record

ArticleBiomimetics (Basel, Switzerland)2026

Biomimetic Spiral-Reinforced Honeycomb for Integrated Energy Absorption Under Complex Loading Scenarios.

Junhao Nian, Zhenyu Huang, Yingsong Zhao, Kai Liu

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2026. 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
0cells of the map it votes in
0citing 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

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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

4 authors.

Junhao NianSchool of Traffic & Transportation Engineering, Central South University, Changsha 410083, China.
Zhenyu HuangSchool of Traffic & Transportation Engineering, Central South University, Changsha 410083, China.
Yingsong ZhaoNational Key Laboratory of Solid Rocket Propulsion, Institute of Xi'an Aerospace Solid Propulsion Technology, Xi'an 710025, China.
Kai LiuSchool of Traffic & Transportation Engineering, Central South University, Changsha 410083, China.ORCID 0000-0003-1633-7188

Funding

National Key R&D Program of China 2022YFB4300101National Key R&D Program of China 2024YFB4303001
6 · The paper itself

Abstract

Planar honeycomb structures, especially biomimetic hexagonal honeycombs, are widely used in energy-absorbing equipment because of their excellent out-of-plane deformation resistance. However, their significant mechanical anisotropy, manifested by the large discrepancy between out-of-plane and in-plane responses, greatly restricts their broader applications. Inspired by spiral-reinforced thin-walled biological tubular systems, such as animal tracheae and plant vessels, this study proposes a biomimetic reinforcement strategy by embedding spiral structures along the thin walls of planar honeycombs. To validate the feasibility of the proposed design, biomimetic honeycomb specimens were fabricated using 3D-printing technology and tested under compression along different loading directions. Furthermore, a numerical model validated against the experiments was developed to reveal the underlying enhancement mechanism. The results demonstrate that the proposed biomimetic honeycomb preserves the favorable out-of-plane performance of the conventional hexagonal honeycomb, while improving the in-plane energy absorption capacity by up to 70%. The biomimetic spiral reinforcements enable more effective load transfer under multidirectional loading, resulting in a more uniform plastic stress distribution over the entire structure and activating a larger deformation region for energy dissipation. The present work provides a bioinspired strategy for developing lightweight energy-absorbing structures for potential applications in aerospace, rail vehicles, marine engineering, and civil structures.

Indexed as

biomimetic designenergy-absorbing materialsSEAspiral structure

Identifiers

PMID42041507
PMCPMC13113431

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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.