Open AccessFlexible 3D memristor array for binary storage and multi‐states neuromorphic computing applications
Author(s) -
Wang TianYu,
Meng JiaLin,
Chen Lin,
Zhu Hao,
Sun QingQing,
Ding ShiJin,
Bao WenZhong,
Zhang David Wei
Publication year - 2021
Publication title -
infomat
Language(s) - English
Resource type - Journals
ISSN - 2567-3165
DOI - 10.1002/inf2.12158
Subject(s) - neuromorphic engineering , memristor , resistive random access memory , emulation , computer science , computer data storage , materials science , computer architecture , electronic engineering , computer hardware , engineering , electrical engineering , artificial neural network , artificial intelligence , voltage , economics , economic growth
The demand of flexible neuromorphic computing electronics is increasing with the rapid development of wearable artificial intelligent devices. The flexible resistive random‐access memory (RRAM) is one excellent candidate of high‐density storage devices. However, due to the limitations of fabrication process, materials system and device structure, it is difficult to prepare flexible 3D high‐density network for neuromorphic computing. In this paper, a 3D flexible memristors network is developed via low‐temperature atomic layer deposition (ALD) at 130°C, with potential of extending to various flexible electronics. The typical bipolar switching characteristics are verified in RRAM units of 3D network, including first, second and third layers. Besides binary storage, the multibit storage in single unit is demonstrated and the storage density is further increased. As a connection link between binary storage and brain‐inspired neuromorphic computing, the multibit storage capability paves the way for the tunable synaptic plasticity, for example, long‐term potentiation/depression (LTP/LTD). The 3D memristors network successfully mimicked the typical neuromorphic functionality and realized ultra‐multi conductance states modulation under 600 spikes. The robust mechanical flexibility is further demonstrated via LTP/LTD emulation under bending states (radius = 10 mm). The 3D flexible memristors network shows significant potential of applications in high‐performance, high‐density and reliable wearable neuromorphic computing system.