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用于原位传感-存储-计算的电荷选择性二维异质界面驱动多功能浮栅存储器

Charge-Selective 2D Heterointerface-Driven Multifunctional Floating Gate Memory for In Situ Sensing-Memory-Computing.

作者信息

Li Ce, Chen Xi, Zhang Zirui, Wu Xiaoshan, Yu Tianze, Bie Ruitong, Yang Dongliang, Yao Yugui, Wang Zhongrui, Sun Linfeng

机构信息

Centre for Quantum Physics, Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE), School of Physics, Beijing Institute of Technology, Beijing 100081, People's Republic of China.

Beijing Key Lab of Nanophotonics & Ultrafine Optoelectronic Systems, School of Physics, Beijing Institute of Technology, Beijing 100081, China.

出版信息

Nano Lett. 2024 Nov 27;24(47):15025-15034. doi: 10.1021/acs.nanolett.4c03828. Epub 2024 Oct 25.

Abstract

Flash memory, dominating data storage due to its substantial storage density and cost efficiency, faces limitations such as slow response, high operating voltages, absence of optoelectronic response, etc., hindering the development of sensing-memory-computing capability. Here, we present an ultrathin platinum disulfide (PtS)/hexagonal boron nitride (hBN)/multilayer graphene (MLG) van der Waals heterojunction with atomically sharp interfaces, achieving selective charge tunneling behavior and demonstrating ultrafast operations, a high on/off ratio (10), extremely low operating voltage, robust endurance (10 cycles), and retention exceeding 10 years. Additionally, we achieve highly linear synaptic potentiation and depression, and observe the reversibly gate-tunable transitions between positive and negative photoconductivity. Furthermore, we employed the VGG11 neural network for in situ trained in-sensor-memory-computing to classify the CIFAR-10 data set, pushing accuracy levels comparable to pure digital systems. This work could pave the way for seamlessly integrated sensing, memory, and computing capabilities for diverse edge computing.

摘要

闪存因其高存储密度和成本效益而在数据存储领域占据主导地位,但它面临着诸如响应速度慢、工作电压高、缺乏光电响应等限制,阻碍了传感 - 存储 - 计算能力的发展。在此,我们展示了一种具有原子级清晰界面的超薄二硫化铂(PtS)/六方氮化硼(hBN)/多层石墨烯(MLG)范德华异质结,实现了选择性电荷隧穿行为,并展示了超快操作、高开/关比(10)、极低的工作电压、强大的耐久性(10 次循环)以及超过 10 年的保持时间。此外,我们实现了高度线性的突触增强和抑制,并观察到正负光电导率之间的可逆栅极可调转变。此外,我们采用 VGG11 神经网络进行原位训练的传感器内存储计算,以对 CIFAR - 10 数据集进行分类,推动了与纯数字系统相当的准确率水平。这项工作可以为各种边缘计算的传感、存储和计算能力的无缝集成铺平道路。

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