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나노 구조 물리 연구단
나노구조물리 연구단
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Self-selective van der Waals heterostructures for large scale memory array

Cited 3 time in webofscience Cited 3 time in scopus
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Title
Self-selective van der Waals heterostructures for large scale memory array
Author(s)
Linfeng Sun; Yishu Zhang; Gyeongtak Han; Geunwoo Hwang; Jinbao Jiang; Bomin Joo; Kenji Watanabe; Takashi Taniguchi; Young-Min Kim; Woo Jong Yu; Bai-Sun Kong; Rong Zhao; Heejun Yang
Publication Date
2019-07
Journal
NATURE COMMUNICATIONS, v.10, no., pp.3161 -
Publisher
NATURE PUBLISHING GROUP
Abstract
The large-scale crossbar array is a promising architecture for hardware-amenable energy efficient three-dimensional memory and neuromorphic computing systems. While accessing a memory cell with negligible sneak currents remains a fundamental issue in the crossbar array architecture, up-to-date memory cells for large-scale crossbar arrays suffer from process and device integration (one selector one resistor) or destructive read operation (complementary resistive switching). Here, we introduce a self-selective memory cell based on hexagonal boron nitride and graphene in a vertical heterostructure. Combining nonvolatile and volatile memory operations in the two hexagonal boron nitride layers, we demonstrate a self-selectivity of 10(10) with an on/off resistance ratio larger than 10(3). The graphene layer efficiently blocks the diffusion of volatile silver filaments to integrate the volatile and non-volatile kinetics in a novel way. Our self-selective memory minimizes sneak currents on large-scale memory operation, thereby achieving a practical readout margin for terabit-scale and energy-efficient memory integration. © The Author(s) 2019
URI
https://pr.ibs.re.kr/handle/8788114/6136
ISSN
2041-1723
Appears in Collections:
Center for Integrated Nanostructure Physics(나노구조물리 연구단) > Journal Papers (저널논문)
Files in This Item:
Self-selective_Nature Communications_Young-Min Kim.pdfDownload

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