材料科学
晶体管
可穿戴计算机
电化学
可穿戴技术
离子键合
聚合物
离子液体
纳米技术
光电子学
工程物理
离子
电极
电气工程
计算机科学
电压
复合材料
嵌入式系统
有机化学
物理化学
工程类
催化作用
化学
作者
Yifei He,Zhaolin Ge,Zhiyang Li,Zhaoxian Li,Riping Liu,Limei Zhang,Liuyuan Lan,Wan Yue,Zhuang Xie
标识
DOI:10.1002/adfm.202415595
摘要
Abstract Wearable near/in‐sensor neuromorphic computing is driving next‐generation human‐artificial intelligence (AI) interface, the Internet of Things, and intelligent robots, with reservoir computing (RC) playing a pivotal role in advancing AI hardware, yet its potential remains underexplored. Herein, an all‐polymer accumulation‐mode organic electrochemical synaptic transistor (OEST) is demonstrated with controlled ionic dynamics that can facilitate high‐performance wearable RC while allowing entire recyclability. A microporous glycolated conjugated polymer channel (P3gCPDT‐1gT2) affords current output above mA level at <1 V and enables both volatile and non‐volatile modes in combination with soft poly(3,4‐ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS)/sorbitol electrodes and electrolytes (gelatin/glycerol). Particularly, modulation of the volatile OESTs as nonlinear dynamic reservoirs are elucidated by tuning ionic dynamics with applied voltages and gel compositions. Moreover, such an all‐polymer device exhibits synaptic performance preservation over >3000 bending cycles and allows convenient recyclability using eco‐friendly solvents. A wearable and sustainable RC system can be thus established by configuring the volatile units for data processing and the nonvolatile units as the weight storage in a single‐layer perceptron readout. Such a simple platform achieves up to 90% accuracy in voice recognition tasks under bending. Thus, this work facilitates the widespread integration of multifunctional organic electronic hardware for implementing intelligent information processing with low‐cost, body‐conformable, and eco‐benign features.
科研通智能强力驱动
Strongly Powered by AbleSci AI