Vertical‐organic‐nanocrystal‐arrays for crossbar memristors with tuning switching dynamics toward neuromorphic computing. (25th February 2021)

• Record Type: Journal Article
• Authors: Yang, Fangxu; Sun, Lingjie; Duan, Qingxi; Dong, Huanli; Jing, Zhaokun; Yang, Yuchao; Li, Rongjin; Zhang, Xiaotao; Hu, Wenping; Chua, Leon
• Is Part Of: SmartMat. Volume 2:Number 1(2021)
• Page Start: 99
• Page End: 108
• Publication Date: 2021-02-25
• Subjects: conducting filament -- memristor -- organic electronics -- organic single crystal; Smart materials -- Periodicals; Materials science -- Periodicals; 620.11
• DOI: 10.1002/smm2.1022
• Languages: English
• ISSNs: 2688-819X

Abstract

Abstract: Memristors proposed by Leon Chua provide a new type of memory device for novel neuromorphic computing applications. However, the approaching of distinct multi‐intermediate states for tunable switching dynamics, the controlling of conducting filaments (CFs) toward high device repeatability and reproducibility, and the ability for large‐scale preparation devices, remain full of challenges. Here, we show that vertical‐organic‐nanocrystal‐arrays (VONAs) could make a way toward the challenges. The perfect one‐dimensional structure of the VONAs could confine the CFs accurately with fine‐tune resistance states in a broad range of 10 3 ratios. The availability of large‐area VONAs makes the fabrication of large‐area crossbar memristor arrays facilely, and the analog switching characteristic of the memristors is to effectively imitate different kinds of synaptic plasticity, indicating their great potential in future applications. Abstract : In this study, vertical‐organic‐nanocrystal‐arrays (VONAs) was developed to construct high‐performance memristors. The unique nanostructure of VONAs could confine conducting filaments accurately, showing fine resistance tuning in a broad ratio. The availability of large‐area VONAs makes the fabrication of large‐area crossbar memristor arrays facilely, and their analog switching characteristic is effective to imitate different kinds of synaptic plasticity, indicating their great potential in future applications.