Wang Shenglong, Yao Yelan, Deng Weili, Chu Xiang, Yang Tao, Tian Guo, Ao Yong, Sun Yue, Lan Boling, Ren Xiarong, Li Xuelan, Xu Tianpei, Huang Longchao, Liu Yang, Lu Jun, Yang Weiqing
Key Laboratory of Advanced Technologies of Materials (Ministry of Education), School of Materials Science and Engineering, Southwest Jiaotong University, Chengdu, Sichuan 610031, People's Republic of China.
School of Chemistry, Southwest Jiaotong University, Chengdu, Sichuan 610031, People's Republic of China.
ACS Nano. 2024 Apr 30;18(17):11183-11192. doi: 10.1021/acsnano.4c00112. Epub 2024 Apr 17.
E-skins, capable of responding to mechanical stimuli, hold significant potential in the field of robot haptics. However, it is a challenge to obtain e-skins with both high sensitivity and mechanical stability. Here, we present a bioinspired piezoresistive sensor with hierarchical structures based on polyaniline/polystyrene core-shell nanoparticles polymerized on air-laid paper. The combination of laser-etched reusable templates and sensitive materials that can be rapidly synthesized enables large-scale production. Benefiting from the substantially enlarged deformation of the hierarchical structure, the developed piezoresistive electronics exhibit a decent sensitivity of 21.67 kPa and a subtle detection limit of 3.4 Pa. Moreover, an isolation layer is introduced to enhance the interface stability of the e-skin, with a fracture limit of 66.34 N/m. Furthermore, the e-skin can be seamlessly integrated onto gloves without any detachment issues. With the assistance of deep learning, it achieves a 98% accuracy rate in object recognition. We anticipate that this strategy will render e-skin with more robust interfaces and heightened sensing capabilities, offering a favorable pathway for large-scale production.
能够响应机械刺激的电子皮肤在机器人触觉领域具有巨大潜力。然而,获得兼具高灵敏度和机械稳定性的电子皮肤是一项挑战。在此,我们展示了一种基于在气流成网纸上聚合的聚苯胺/聚苯乙烯核壳纳米粒子的具有分层结构的仿生压阻传感器。激光蚀刻的可重复使用模板与可快速合成的敏感材料相结合,实现了大规模生产。得益于分层结构大幅增大的形变,所开发的压阻电子器件展现出21.67 kPa的良好灵敏度和3.4 Pa的细微检测极限。此外,引入了一个隔离层以增强电子皮肤的界面稳定性,其断裂极限为66.34 N/m。再者,该电子皮肤可以无缝集成到手套上,不存在任何脱落问题。在深度学习的辅助下,它在物体识别方面达到了98%的准确率。我们预计,这一策略将使电子皮肤具有更稳健的界面和更高的传感能力,为大规模生产提供一条有利途径。