用于大规模存储阵列的自选范德华异质结构

大规模交叉开关阵列是一种适用于硬件的高能效三维存储器和神经形态计算系统的有前途的体系结构。虽然在交叉开关阵列架构中访问具有可忽略的潜电流的存储单元仍然是一个基本问题，但用于大型交叉开关阵列的最新存储单元遭受过程和设备集成（一个选择器和一个电阻器）或破坏性读取操作（互补性）的困扰。电阻切换）。在这里，我们介绍了一种基于垂直异质结构的六方氮化硼和石墨烯的自选存储单元。结合两个六边形氮化硼层中的非易失性和挥发性存储操作，我们展示了1010的自选择性，其开/关电阻比大于103。石墨烯层有效地阻止了挥发性银丝的扩散，从而整合了挥发性和非挥发性-挥发性动力学以新颖的方式。我们的自选存储器最大程度地减少了大规模存储器运行时的潜电流，从而为TB级和节能型存储器集成提供了实用的读取余量。

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 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.