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利用固态有机电化学晶体管中的空间离子动力学进行多触觉传感与处理

Exploiting Spatial Ionic Dynamics in Solid-State Organic Electrochemical Transistors for Multi-Tactile Sensing and Processing.

作者信息

Hou Kunqi, Chen Shuai, John Rohit Abraham, He Qiang, Zhou Zhongliang, Mathews Nripan, Lew Wen Siang, Leong Wei Lin

机构信息

School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore, 637371, Singapore.

School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore.

出版信息

Adv Sci (Weinh). 2024 Nov;11(43):e2405902. doi: 10.1002/advs.202405902. Epub 2024 Sep 27.

DOI:10.1002/advs.202405902
PMID:39331857
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11578318/
Abstract

The human nervous system inspires the next generation of sensory and communication systems for robotics, human-machine interfaces (HMIs), biomedical applications, and artificial intelligence. Neuromorphic approaches address processing challenges; however, the vast number of sensors and their large-scale distribution complicate analog data manipulation. Conventional digital multiplexers are limited by complex circuit architecture and high supply voltage. Large sensory arrays further complicate wiring. An 'in-electrolyte computing' platform is presented by integrating organic electrochemical transistors (OECTs) with a solid-state polymer electrolyte. These devices use synapse-like signal transport and spatially dependent bulk ionic doping, achieving over 400 times modulation in channel conductance, allowing discrimination of locally random-access events without peripheral circuitry or address assignment. It demonstrates information processing from 12 tactile sensors with a single OECT output, showing clear advantages in circuit simplicity over existing all-electronic, all-digital implementations. This self-multiplexer platform offers exciting prospects for circuit-free integration with sensory arrays for high-quality, large-volume analog signal processing.

摘要

人类神经系统为机器人技术、人机接口(HMI)、生物医学应用和人工智能的下一代传感与通信系统提供了灵感。神经形态方法解决了处理挑战;然而,大量的传感器及其大规模分布使模拟数据处理变得复杂。传统的数字多路复用器受到复杂电路架构和高电源电压的限制。大型传感阵列进一步使布线复杂化。通过将有机电化学晶体管(OECT)与固态聚合物电解质集成,提出了一种“电解质内计算”平台。这些器件使用类似突触的信号传输和空间相关的体离子掺杂,在沟道电导中实现了超过400倍的调制,无需外围电路或地址分配即可区分局部随机访问事件。它展示了利用单个OECT输出对12个触觉传感器进行信息处理,与现有的全电子、全数字实现相比,在电路简单性方面具有明显优势。这种自多路复用器平台为与传感阵列进行无电路集成以实现高质量、大容量模拟信号处理提供了令人兴奋的前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cb8/11578318/45b391dc179e/ADVS-11-2405902-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cb8/11578318/3fe9b1784e73/ADVS-11-2405902-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cb8/11578318/f412e0736bcf/ADVS-11-2405902-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cb8/11578318/7d2b4d0ed29c/ADVS-11-2405902-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cb8/11578318/45b391dc179e/ADVS-11-2405902-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cb8/11578318/3fe9b1784e73/ADVS-11-2405902-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cb8/11578318/f412e0736bcf/ADVS-11-2405902-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cb8/11578318/7d2b4d0ed29c/ADVS-11-2405902-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cb8/11578318/45b391dc179e/ADVS-11-2405902-g005.jpg

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本文引用的文献

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