PEDOT-ZnO Nanoparticle Hybrid Film-Based Memristors for Synapse Emulation in Neuromorphic Computing Applications
Jiaming Fan, Jiang Feng, Yu Gao, Zijian Zhang, Song Xue, Gangri Cai, Jinshi Zhao
Abstract
Synapses and neurons in artificial intelligence are acknowledged as pivotal elements in constructing neuromorphic computing systems. Specifically, organic material-based memristors are widely recognized due to their advantages in terms of transparency, flexibility, cost-effectiveness, environment friendliness, and biocompatible properties. In this paper, we fabricated organic functional layer-based memristors and synapses by spin-coating poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate) (PEDOT:PSS) onto an indium tin oxide (ITO) substrate following a magnetron-sputtered ITO as the top electrode. Moreover, zinc oxide nanoparticles (ZnO NPs) were employed in the functional layer as charge trapping elements for optimizing the performance of PEDOT-based memory devices. With control of the concentrations of ZnO NPs, the devices of ITO/PEDOT:PSS(ZnO NPs)/ITO exhibited promising resistive switching performance and synaptic functionalities. In the device of ITO/PEDOT:PSS(3% ZnO NPs)/ITO, it shows gradual switching characteristics and could effectively mimic synapse functionalities. In the device ITO/PEDOT:PSS(5% ZnO NPs)/ITO, it shows a forming-free character and excellent resistive change performance.