A 2D material-based floating gate device with linear synaptic weight update

Eunpyo Park, Minkyung Kim, Tae Soo Kim, In Soo Kim, Jongkil Park, Jaewook Kim, Yeonjoo Jeong, Suyoun Lee, Inho Kim, Jong Keuk Park, Gyu Tae Kim, Jiwon Chang, Kibum Kang, Joon Young Kwak

Research output: Contribution to journalArticlepeer-review

Abstract

Neuromorphic computing is of great interest among researchers interested in overcoming the von Neumann computing bottleneck. A synaptic device, one of the key components to realize a neuromorphic system, has a weight that indicates the strength of the connection between two neurons, and updating this weight must have linear and symmetric characteristics. Especially, a transistor-type device has a gate terminal, separating the processes of reading and updating the conductivity, used as a synaptic weight to prevent sneak path current issues during synaptic operations. In this study, we fabricate a top-gated flash memory device based on two-dimensional (2D) materials, MoS2 and graphene, as a channel and a floating gate, respectively, and Al2O3 and HfO2 to increase the tunneling efficiency. We demonstrate the linear weight updates and repeatable characteristics of applying negative/positive pulses, and also emulate spike timing-dependent plasticity (STDP), one of the learning rules in a spiking neural network (SNN).

Original languageEnglish
Pages (from-to)24503-24509
Number of pages7
JournalNanoscale
Volume12
Issue number48
DOIs
Publication statusPublished - 2020 Dec 28

ASJC Scopus subject areas

  • Materials Science(all)

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