神经形态工程学
突触重量
计算机科学
材料科学
铁电性
异质结
冯·诺依曼建筑
光电子学
人工神经网络
小型化
电子工程
纳米技术
人工智能
工程类
操作系统
电介质
作者
Pu Feng,Sixian He,Zhi Zeng,Congcong Dang,Ming Li,Liancheng Zhao,Dongbo Wang,Liming Gao
标识
DOI:10.1002/admt.202301355
摘要
Abstract Neuromorphic computing systems are based on new architecture inspired by biological learning behavior and biological structure to overcome the shortcomings of the von Neumann system, such as high energy consumption and generation of excessive redundant data. However, common synaptic‐device designs are still need to carry an external power source, which is detrimental to both the miniaturization of smart devices and the further reduction of energy consumption. Therefore, self‐powered optoelectronic synapses hold great promise for achieving energy‐efficient artificial intelligence applications. Given the advantages of heterogeneous integration and ferroelectric performance, the 2D ferroelectric In 2 Se 3 has become a typical candidate material for biological synaptic devices and neuromorphic computing. Although, various structures of ferroelectric synaptic devices are developed, most of which are controlled by optical or electrical pulses, hardly any reports discuss the operation in self‐powered mode. In this work, an In 2 Se 3 /MoS 2 ferroelectric lateral heterojunction‐type optoelectronic synaptic device is fabricated to mimic biological synaptic functions in voltage mode or self‐driven mode. In addition, two simplified image pre‐processing methods based on device arrays are shown to improve the recognition accuracy of a back‐end neural network. The proposed approach suggests a new route for designing and applying high‐performance synaptic devices.
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