journal article·2026-02-01Open access

An aircell hydrogel for ultra-sensitive human-machine interaction

Minghao Li, Haoxu Yu, Deliang Li, Fujun Wang, Yanling Tian, Ye Tian, Faze Chen

Abstract

Abstract Porous hydrogel sensors have attracted significant attention in fields such as smart wearables and medical monitoring due to their high sensitivity. However, existing fabrication methods typically degrade the surface smoothness of hydrogels when introducing porous structures and face significant challenges in removing fillers completely. To address these challenges, we herein introduce a novel one-step, thermosensitive spray-coating technique for the preparation of aircell hydrogel (ACH). This method leverages the rapid cooling of a thermoresponsive gelatin methacryloyl solution through atomization, enabling rapid cross-linking within seconds and air bubbles encapsulated in situ. Additionally, the transient flow of the pre-gel facilitates the repair of voids formed by ruptured surface bubbles, leading to the creation of the ACH with uniformly distributed inner air bubbles and a smooth outer surface. The mold-free fabrication method is independent of substrate surface properties, enabling the creation of a porous hydrogel film with a thickness as thin as 163 μm. Furthermore, the dual-crosslinked network endows the ACH with excellent anti-swelling properties, and the physical crosslinking between gelatin molecules allows the ACH to self-heal. The ACH exhibits excellent sensitivity in deformation sensing and can even successfully track minor external forces, which enables it to effectively complete various tasks such as facial expression recognition, pitch differentiation, and motion detection. By integrating the ACH into a sensing glove, we also demonstrate the significant potential of the ACH for applications in human-machine interaction and tactile sensing. Ultimately, the ACH sensors are also applied to motion mapping and machine tactile feedback, indicating their promising potential in human-machine interaction.
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Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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