Ferroelectrically modulated ion dynamics in Li+ electrolyte-gated transistors for neuromorphic computing

神经形态工程学 材料科学 电解质 晶体管 离子 电导 光电子学 计算机科学 化学物理 纳米技术 人工神经网络 电压 物理 化学 人工智能 电极 凝聚态物理 有机化学 物理化学 量子力学
作者
Minho Jin,Haeyeon Lee,Jae‐Hak Lee,Daeyoung Han,Changik Im,Jiyeon Kim,Moongu Jeon,Eungkyu Lee,Youn Sang Kim
出处
期刊:Applied physics reviews [American Institute of Physics]
卷期号:10 (1) 被引量:29
标识
DOI:10.1063/5.0130742
摘要

Li+ electrolyte-gated transistors (EGTs) have attracted significant attention as artificial synapses because of the fast response of Li+ ion, low operating voltage, and applicability to flexible electronics. Due to the inherent nature of Li+ ion, Li+ EGTs show, however, limitations, such as poor long-term synaptic plasticity and nonlinear/nonsymmetric conductance update, which hinder the practical applications of artificial synapses. Herein, Li+ EGTs integrated with poly(vinylidene fluoride-co-trifluoroethylene) (PVDF-TrFE) ferroelectric polymer as a channel–electrolyte interlayer are presented. Owing to the polarized domains of PVDF-TrFE, the transport of Li+ ions at the channel–electrolyte interface is accelerated, and Li+ ions effectively penetrate the channel. Moreover, the self-diffusion of Li+ ions from the channel to the electrolyte is suppressed by the downward polarized domains. Li+ EGTs, therefore, successfully demonstrate synaptic characteristics, including excitatory postsynaptic current, short-/long-term synaptic plasticity, and paired-pulse facilitation. Also, conductance update in Li+ EGTs shows a dynamic range (Gmax/Gmin) of 92.42, high linearity, and distinct stability over 100 cycles. Based on their synaptic characteristics, inference simulations using a convolution neural network for the CIFAR-10 dataset imply that Li+ EGTs are suitable as artificial synapses with an inference accuracy of 89.13%. The new methodological approach addressing modulation of ion dynamics at the interface is introduced for developing practical synaptic devices.
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