Nanoscale wedge resistive-switching synaptic device and experimental verification of vector-matrix multiplication for hardware neuromorphic application

Min Hwi Kim, Seongjae Cho, Byung Gook Park

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

In this work, nanoscale wedge-structured silicon nitride (SiNx)-based resistive-switching random-access memory with data non-volatility and conductance graduality has been designed, fabricated, and characterized for its application in the hardware neuromorphic system. The process integration with full Si-processing-compatibility for constructing the unique wedge structure by which the electrostatic effects in the synaptic device operations are maximized is demonstrated. The learning behaviors of the fabricated synaptic devices are shown. In the end, vector-matrix multiplication is experimentally verified in the array level for application in more energy-efficient hardware-driven neuromorphic systems.

Original languageEnglish
Article number050905
JournalJapanese Journal of Applied Physics
Volume60
Issue number5
DOIs
StatePublished - May 2021

Bibliographical note

Publisher Copyright:
© 2021 The Japan Society of Applied Physics.

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