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揭示压电离子效应中的门控行为:迈向神经拟态触觉传感。

Unveiling Gating Behavior in Piezoionic Effect: toward Neuromimetic Tactile Sensing.

机构信息

College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, 110819, China.

School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing, 100081, China.

出版信息

Adv Mater. 2024 Sep;36(36):e2405391. doi: 10.1002/adma.202405391. Epub 2024 Jul 26.

DOI:10.1002/adma.202405391
PMID:39056155
Abstract

The human perception system's information processing is intricately linked to the nonlinear response and gating effect of neurons. While piezoionics holds potential in emulating the pressure sensing capability of biological skin, the incorporation of information processing functions seems neglected. Here, ionic gating behavior in piezoionic hydrogels is uncovered as a notable extension beyond the previously observed linear responses. The hydrogel can generate remarkably high voltages (700 mV) and currents (7 mA) when indentation forces surpass the threshold. Through a comprehensive analysis involving simulations and experimental investigations, it is proposed that the gating behavior emerges due to significant diffusion differences between cations and anions. To showcase the practical implications of this breakthrough, the piezoionic hydrogels are successfully integrated with prostheses and robot hands, demonstrating that the gating effect enables accurate discrimination between gentle and harsh touch. The advancement in neuromimetic tactile sensing has significant potential for emerging applications such as humanoid robotics and biomedical engineering, offering valuable opportunities for further development of embodied neuromorphic intelligence.

摘要

人类感知系统的信息处理与神经元的非线性响应和门控效应密切相关。虽然压电器件在模拟生物皮肤的压力传感能力方面具有潜力,但信息处理功能的整合似乎被忽视了。在这里,揭示了压电器凝胶中的离子门控行为是对先前观察到的线性响应的显著扩展。当压痕力超过阈值时,水凝胶可以产生高达 700 mV 的高电压和 7 mA 的大电流。通过涉及模拟和实验研究的综合分析,提出了门控行为是由于阳离子和阴离子之间显著的扩散差异引起的。为了展示这一突破的实际意义,压电器凝胶已成功集成到假肢和机器手中,证明门控效应能够准确区分轻柔触摸和粗暴触摸。神经拟态触觉传感的进步为仿人机器人和生物医学工程等新兴应用提供了巨大的潜力,为嵌入式神经形态智能的进一步发展提供了有价值的机会。

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