Liu Xiaoxian, Wang Shuiyuan, Di Ziye, Wu Haoqi, Liu Chunsen, Zhou Peng
Shanghai Key Lab for Future Computing Hardware and System, School of Microelectronics, Fudan University, Shanghai, 200433, China.
Frontier Institute of Chip and System & Qizhi Institute, Fudan University, Shanghai, 200433, China.
Adv Sci (Weinh). 2023 Aug;10(22):e2301851. doi: 10.1002/advs.202301851. Epub 2023 May 25.
Neuromorphic computing can efficiently handle data-intensive tasks and address the redundant interaction required by von Neumann architectures. Synaptic devices are essential components for neuromorphic computation. 2D phosphorene, such as violet phosphorene, show great potential in optoelectronics due to their strong light-matter interactions, while current research is mainly focused on synthesis and characterization, its application in photoelectric devices is vacant. Here, the authors combined violet phosphorene and molybdenum disulfide to demonstrate an optoelectronic synapse with a light-to-dark ratio of 10 , benefiting from a significant threshold shift due to charge transfer and trapping in the heterostructure. Remarkable synaptic properties are demonstrated, including a dynamic range (DR) of > 60 dB, 128 (7-bit) distinguishable conductance states, electro-optical dependent plasticity, short-term paired-pulse facilitation, and long-term potentiation/depression. Thanks to the excellent DR and multi-states, high-precision image classification with accuracies of 95.23% and 79.65% is achieved for the MNIST and complex Fashion-MNIST datasets, which is close to the ideal device (95.47%, 79.95%). This work opens the way for the use of emerging phosphorene in optoelectronics and provides a new strategy for building synaptic devices for high-precision neuromorphic computing.
神经形态计算能够高效处理数据密集型任务，并解决冯·诺依曼架构所需的冗余交互问题。突触器件是神经形态计算的关键组件。二维磷烯，如紫磷烯，因其强光 - 物质相互作用在光电子学中展现出巨大潜力，然而目前的研究主要集中在合成与表征方面，其在光电器件中的应用尚属空白。在此，作者将紫磷烯与二硫化钼相结合，展示了一种光暗比为10的光电突触，这得益于异质结构中电荷转移和俘获导致的显著阈值变化。该突触展现出卓越的突触特性，包括大于60 dB的动态范围（DR）、128种（7位）可区分的电导状态、电光依赖可塑性、短期双脉冲易化以及长期增强/抑制。得益于出色的动态范围和多状态特性，对于MNIST和复杂的Fashion - MNIST数据集，实现了精度分别为95.23%和79.65%的高精度图像分类，接近理想器件的精度（95.47%，79.95%）。这项工作为新兴磷烯在光电子学中的应用开辟了道路，并为构建用于高精度神经形态计算的突触器件提供了新策略。
