Bend‐Resistant and Energy‐Friendly GO‐PVA/PVA Polymer Electret Synaptic Transistors for Neuromorphic Computations

材料科学 神经形态工程学 驻极体 晶体管 光电子学 电压 人工神经网络 计算机科学 复合材料 电气工程 人工智能 工程类
作者
Xiao Fu,Zhihao Liang,Wentao Shuai,Yushan Li,Honglong Ning,Guoping Su,Xubing Lu,Weiguang Xie,Rihui Yao,Junbiao Peng
出处
期刊:Advanced Functional Materials [Wiley]
卷期号:33 (52) 被引量:25
标识
DOI:10.1002/adfm.202308127
摘要

Abstract Polymer electret synaptic transistor is a promising three‐terminal artificial synaptic device. In this work, the electrical characteristics of the composite insulator and transistor are enhanced by modulating the concentration of the 2D nanofiller graphene oxide (GO) and the stacked film structure based on a polyvinyl alcohol (PVA) matrix. The GO‐PVA/PVA polymer electret synaptic transistors before and after dynamic/static bending exhibit typical synaptic characteristics, including short‐term plasticity, long‐term plasticity, pair‐pulse facilitation, spike‐timing‐dependent plasticity, and “learning–forgetting–relearning” features. Importantly, the device exhibits good cycling stability, uniformity and linearity in the potentiation‐depression cycling test, which is beneficial for improving the accuracy of neuromorphic computations. Also, it shows extremely low energy consumption (≈0.32 fJ). The recognition accuracy of images is simulated based on the constructed artificial neural network, which achieves 86.8% for the MNIST dataset. In addition, the devices maintain high recognition accuracy after dynamic/static bending, indicating that the devices are extremely bend‐resistant. The GO‐PVA/PVA polymer electret synaptic transistor is expected to be a potential candidate for neuromorphic computations and electronic skin.
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