Flexible random resistive access memory devices with ferrocene-rGO nanocomposites for artificial synapses

Random resistive access memory (RRAM) devices with a simple structure, low power consumption, and tunable switching behavior have emerged as promising candidates to simulate biological synapses. Here, we demonstrate solution-processable RRAM devices with FeC-rGO nanocomposites by intercalating nano-...

Full description

Saved in:
Bibliographic Details
Published in:Journal of materials chemistry. C, Materials for optical and electronic devices Materials for optical and electronic devices, 2021-05, Vol.9 (17), p.5749-5757
Main Authors: Zhou, Jiankui, Feng, Hanfang, Wang, Yadong, Sun, Qingqing, Liu, Yingliang, Liu, Xuying, Zhang, Li, Cao, Shaokui
Format: Article
Language:English
Subjects:
Artificial intelligence
Bend radius
Bending machines
Data storage
Electric potential
Ferrocenes
Graphene
Information storage
Memory devices
Nanocomposites
Object recognition
Pattern recognition
Power consumption
Scanning electron microscopy
Sheets
Spin coating
Synapses
Voltage
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Random resistive access memory (RRAM) devices with a simple structure, low power consumption, and tunable switching behavior have emerged as promising candidates to simulate biological synapses. Here, we demonstrate solution-processable RRAM devices with FeC-rGO nanocomposites by intercalating nano-aggregating ferrocenes (FeCs) between the reduced graphene oxide (rGO) sheets, in which FeCs anchor on the surface of rGO through π-π stacking interactions. The Al/FeC-rGO/ITO devices fabricated by spin-coating exhibit a low SET/RESET voltage of −1.7 V/+2.1 V and a high ON/OFF ratio of 10 8 , which results from the formation/rupture of conductive paths between rGO sheets gated by the redox of FeCs. Besides, the devices show high repeatability, excellent durability and favorable flexibility. In addition, the obtained device can be utilized to simulate the potentiation and depression of synapses by applying a pulse voltage below V SET , further contributing to image pattern recognition. Thus, this approach aims to fabricate information storage devices for future use in artificial intelligence. Flexible RRAM devices based on redox active ferrocene-rGO nanocomposites exhibit an enhanced ON/OFF ratio of 10 8 and synapse simulations simultaneously.
ISSN:2050-7526
2050-7534
DOI:10.1039/d1tc00227a