材料科学
光电子学
异质结
二硫化钼
计算机科学
非易失性存储器
电压
能源消耗
人工神经网络
纳米技术
电气工程
神经形态工程学
电子工程
人工智能
工程类
冶金
作者
Yanan Wang,Yue Zheng,Jing Gao,Tengyu Jin,Enlong Li,Xu Lian,Xuan Pan,Cheng Han,Huipeng Chen,Wei Chen
出处
期刊:InfoMat
[Wiley]
日期:2021-07-13
卷期号:3 (8): 917-928
被引量:89
摘要
Abstract Two‐dimensional (2D) van der Waals heterostructure (vdWH)‐based floating gate devices show great potential for next‐generation nonvolatile and multilevel data storage memory. However, high program voltage induced substantial energy consumption, which is one of the primary concerns, hinders their applications in low‐energy‐consumption artificial synapses for neuromorphic computing. In this study, we demonstrate a three‐terminal floating gate device based on the vdWH of tin disulfide (SnS 2 ), hexagonal boron nitride (h‐BN), and few‐layer graphene. The large electron affinity of SnS 2 facilitates a significant reduction in the program voltage of the device by lowering the hole‐injection barrier across h‐BN. Our floating gate device, as a nonvolatile multilevel electronic memory, exhibits large on/off current ratio (~10 5 ), good retention (over 10 4 s), and robust endurance (over 1000 cycles). Moreover, it can function as an artificial synapse to emulate basic synaptic functions. Further, low energy consumption down to ~7 picojoule (pJ) can be achieved owing to the small program voltage. High linearity (<1) and conductance ratio (~80) in long‐term potentiation and depression (LTP/LTD) further contribute to the high pattern recognition accuracy (~90%) in artificial neural network simulation. The proposed device with attentive band engineering can promote the future development of energy‐efficient memory and neuromorphic devices. image
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