神经形态工程学
多路复用器
计算机科学
信号处理
晶体管
触觉传感器
电子工程
纳米技术
材料科学
电气工程
数字信号处理
多路复用
计算机硬件
人工智能
电压
电信
人工神经网络
工程类
机器人
作者
Kunqi Hou,Shuai Chen,Rohit Abraham John,Qiang He,Zhongliang Zhou,Nripan Mathews,Wen Siang Lew,Wei Lin Leong
出处
期刊:Advanced Science
[Wiley]
日期:2024-09-27
卷期号:11 (43): e2405902-e2405902
被引量:6
标识
DOI:10.1002/advs.202405902
摘要
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.
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