Evidence map›Paper›PMID 41878805›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

The Elephant Trunk Skin Inspires a Highly Sensitive and Deformable, Yet Robust, Armor Skin.

Jun Chang Yang, Petr Trunin, Behnam Kamare, Lucia Beccai

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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.

Jun Chang YangSoft BioRobotics Perception Lab, Istituto Italiano di Tecnologia, Genova, Italy.
Petr TruninSoft BioRobotics Perception Lab, Istituto Italiano di Tecnologia, Genova, Italy.
Behnam KamareSoft BioRobotics Perception Lab, Istituto Italiano di Tecnologia, Genova, Italy.
Lucia BeccaiSoft BioRobotics Perception Lab, Istituto Italiano di Tecnologia, Genova, Italy.ORCID https://orcid.org/0000-0002-8754-5155

Funding

European Union's Horizon 2020 program 863212Italian Ministry of Foreign Affairs and International Cooperation PGR02061
6 · The paper itself

Abstract

Soft artificial skins attract significant attention due to the inherent high deformability and tactile sensing functions, making them highly beneficial for skin-attachable electronics and robotics. However, they have limited mechanical robustness, which is a requirement for real-world applications. Therefore, an evolution to soft "armor skins" is necessary, where deformation, tactile sensitivity, and ruggedness co-exist. We look at the elephant trunk skin as a remarkable model that due to its unique hierarchical structure deforms freely accommodating the trunk versatile motions while maintaining mechanical robustness, providing protection while also allowing for highly sensitive touch. Inspired by this we present the elephant trunk-inspired armor skin with tactile sensing (ETATS), which exhibits high deformability, resistance to puncture and tear, tactile and strain sensing capability. The ETATS consists of a folded soft substrate reinforced with aligned fibers, capable of 60% stretchability of 40% compressibility in lateral direction, combined with a rigid hexagonal island array for strong puncture resistance (97.5 N). Morphology-based decoupling of strain and pressure enables large-area pressure and lateral strain sensing in real-time by embedded optical waveguides. Our strategy maximizes the stretchability, protective capability, and sensing performance of electronic skin, making it highly beneficial for applications in both humans and robots.

Indexed as

ElephantsSkinSkin, ArtificialTorsoTouchAnimalsHumansRoboticsarmor skinbio‐inspired skinelephant trunk skinfold structurepuncture resistancetactile sensing

Identifiers

PMID41878805
PMCPMC13252638

What OpenQuestion holds

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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.