Wei Chao, Yu Shifan, Meng Yifan, Xu Yijing, Hu Yu, Cao Zhicheng, Huang Zijian, Liu Lei, Luo Yanhao, Chen Hongyu, Chen Zhong, Zhang Zeliang, Wang Liang, Zhao Zhenyu, Zheng Yuanjin, Liao Qingliang, Liao Xinqin
Department of Electronic Science, Xiamen University, Xiamen, 361005, China.
Department of Engineering Mechanics, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
Adv Mater. 2025 Jul;37(27):e2420501. doi: 10.1002/adma.202420501. Epub 2025 Apr 28.
Electronics continue to drive technological innovation and diversified applications. To ensure efficiency and effectiveness across various interactive contexts, the ability to adjust operating functions or parameters according to environmental shifts or user requirements is highly desirable. However, due to the inherent limitations of nonadaptive device structures and materials, the current development of touch electronics faces challenges, e.g., limited hardware resources, poor adaptability, weak deformation stability, and bottlenecks in sensing data processing. Here, a reconfigurable and adaptive intelligent (RAI) touch sensor is proposed, inspired by octopus's tentacle cognitive behavior. It realizes remarkable deformability and highly efficient multitouch interactions. The geometric progression structure of the sensing element equips the RAI touch sensor with a unique integrated-in-sensing mechanism and programmable logic. This greatly compresses sensing data dimensionality at the edge, yielding concise and undistorted interactive signals. By leveraging the advantages of hard-soft bonding and interface modulation of functional materials, the adaptability is achieved with a 200% strain range a 180° twist tolerance, and exceptional deformation stability of >10 000 cycles. The diverse application-specific configurations of the RAI touch sensor, enable a dynamic intention recognition accuracy of over 99%, advancing next-generation Internet of Things and edge computing research and innovation.
电子技术持续推动技术创新和多样化应用。为确保在各种交互环境中的效率和有效性，根据环境变化或用户需求调整操作功能或参数的能力是非常可取的。然而，由于非自适应设备结构和材料的固有局限性，当前触摸电子技术的发展面临挑战，例如硬件资源有限、适应性差、变形稳定性弱以及传感数据处理的瓶颈。在此，受章鱼触手认知行为的启发，提出了一种可重构自适应智能（RAI）触摸传感器。它实现了卓越的可变形性和高效的多点触摸交互。传感元件的几何级数结构为RAI触摸传感器配备了独特的集成传感机制和可编程逻辑。这极大地压缩了边缘的传感数据维度，产生简洁且不失真的交互信号。通过利用功能材料的软硬结合和界面调制优势，在200%的应变范围、180°的扭转容差以及超过10000次循环的卓越变形稳定性下实现了适应性。RAI触摸传感器的多种特定应用配置实现了超过99%的动态意图识别准确率，推动了下一代物联网和边缘计算的研究与创新。
