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Abrasion-resistant wearable skins based on bilayered solid/liquid stretchable conductors
Zejun Wang1, Puyuan Shi2, Yixuan Li3
1Department of Materials Science and Engineering, Central South University, Changsha, China.
Nature Communications
|March 11, 2026
Summary
Researchers developed durable, abrasion-resistant soft electronic skins using a bilayer conductor. These wearable sensors maintain function under extreme conditions, enabling reliable biomonitoring and accurate detection of braille and facial expressions.
Area of Science:
- Materials Science and Engineering
- Bioelectronics
- Wearable Technology
Background:
- Soft bioelectronic skins are promising for continuous, unobtrusive biomonitoring.
- Existing wearable skins often lack the abrasion resistance of human skin.
- Need for durable sensors capable of withstanding mechanical and chemical stresses.
Purpose of the Study:
- To develop abrasion-resistant wearable electronic skins.
- To ensure high conductivity and electromechanical stability under extreme conditions.
- To demonstrate reliable signal capture for biomonitoring applications.
Main Methods:
- Fabrication of a bilayer stretchable conductor architecture using styrene-ethylene-butylene-styrene (SEBS).
- Top layer: silver particle (AgPs)-impregnated SEBS for abrasion resistance.
- Bottom layer: liquid metal particle (LMPs)-impregnated SEBS for high conductivity (>900% strain).
Main Results:
- The ultrathin (13.3 µm) bilayer skins exhibited exceptional durability against abrasion, large deformations, and harsh chemical environments.
- Maintained electromechanical stability during repeated stress tests.
- Successfully captured high-fidelity mechanical and electrophysiological signals in demanding scenarios.
Conclusions:
- The developed bilayer wearable skins offer superior abrasion resistance and durability for next-generation biomonitoring.
- Demonstrated a soft, multimodal system for pressure and biopotential monitoring.
- Achieved high prediction accuracy (98.75%) in applications like braille recognition and facial expression detection.

