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成果发表于2019年7月18日《自然·通讯》

Self-selective van der Waals heterostructures for large scale memory array

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 

DOI：https://doi.org/10.1038/s41467-019-11187-9

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 non-volatile and volatile memory operations in the two hexagonal boron nitride layers, we demonstrate a self-selectivity of 10¹⁰ with an on/off resistance ratio larger than 10³. 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.