神经形态工程学
材料科学
铁电性
图层(电子)
纳米技术
光电子学
计算机科学
人工神经网络
人工智能
电介质
作者
Zongjie Shen,Alei Li,Qinan Wang,Yixin Cao,Yi Sun,Jian Yao,Zhengjun Liu,Yong Zhang,Lixing Kang,Chun Zhao,Zhongming Zeng
标识
DOI:10.1002/adfm.202412832
摘要
Abstract The emergence of 2D van der Waals (vdW) materials, owing to highly tunable electrical conductivity, remarkably free stackability, and excellent compatibility for heterojunction integration, has provided abundant research diversity of artificial synapses. Here, an innovative 2D vdW heterosynaptic memtransistor (vdW‐HT) synapse is proposed with a ferroelectric CuInP 2 S 6 inserted layer. Neuromorphic synaptic weight change of the vdW‐HT synapse in this work are modulated by the synergistic effects of interlayer coupling and ferroelectric polarization reversal. It is the first time to evaluate the required initial energy consumption of ferroelectric vdW‐HT synapses with matrixed biomimetic characteristics of “Learning–Forgetting–Re‐learning–Memorizing.” The required initial energy consumption is only ≈3.06 pJ, which provided supporting evidence to indicate the promising potential of vdW‐HT synapses in exploring neuromorphic applications. A vdW‐HT computing system with artificial recognition capability for intelligent automobiles is established and demonstrated outstanding recognition abilities for multiple targets in various environments. The highest recognition accuracy for pedestrians is 98%. In addition, the excellent recognition property is integrated with a robotic arm, successfully achieving high‐precision grasping behavior and designated position transmission for identified targets. These results provide promising strategies for the integrated development of emerging neuromorphic electronics and industrial applications.
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