A Nature-Inspired Structure Revolutionizes Self-Powered Sensors

Self-powered flexible sensors could well transform the way we monitor health and interact with machines. However, their efficiency often faces a major obstacle: the mechanical mismatch between biological tissues and rigid devices. When a sensor is placed on a moving joint, it gradually detaches, losing contact with the skin and reducing signal quality. To solve this problem, researchers drew inspiration from a rare natural phenomenon: the auxetic effect.

Certain materials, such as lacewing wings, possess a counterintuitive property. Instead of shrinking laterally when stretched, they expand. This behavior, called the auxetic effect, allows these structures to better conform to curved surfaces and resist deformation. By replicating this architecture in the form of hexagonal metastructures, scientists have designed a new type of sensor capable of perfectly adapting to human body movements.

This innovative sensor uses two layers of materials that generate electricity through friction. One is made of modified collagen, the other of micropatterned fluorinated ethylene propylene. When they come into contact and then separate, they produce an electric current. Thanks to the auxetic structure, the sensor maintains close contact with the skin, even during complex movements. It thus converts mechanical energy into electricity with three times the efficiency of conventional sensors, reaching up to 13.8% efficiency in a linear configuration.

The advancement does not stop there. Coupled with an artificial intelligence model, this sensor can recognize objects or gestures with over 98% accuracy. It paves the way for various applications, such as precise motion tracking or the development of more intuitive human-machine interfaces. By combining mechanical adaptability and artificial intelligence, this technology promises to make wearable sensors more reliable, higher performing, and energy autonomous.

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Reference Report

DOI: https://doi.org/10.1007/s40820-026-02125-8

Title: Bioinspired Auxetic Metastructures Enable Biomechanically Adaptive, Machine Learning-Enhanced Self-Powered Sensing with Ultrahigh Efficiency

Journal: Nano-Micro Letters

Publisher: Springer Science and Business Media LLC

Authors: Wei Wang; Xuechuan Wang; Linbin Li; Yi Zhou; Wenlong Zhang; Long Xing; Long Xie; Yitong Wang; Ouyang Yue; Xinhua Liu