神经形态工程学
材料科学
铁磁性
凝聚态物理
自旋电子学
国家(计算机科学)
记忆电阻器
双稳态
磁畴壁(磁性)
光电子学
纳米技术
电子工程
人工神经网络
磁化
人工智能
磁场
物理
计算机科学
工程类
算法
量子力学
作者
Chendi Yang,Yalei Huang,Ke Pei,Xiao Ping Long,Liting Yang,Yongming Luo,Yuxiang Lai,Jincang Zhang,Guixin Cao,Renchao Che
标识
DOI:10.1002/adma.202311831
摘要
Abstract Controlling the multi‐state switching is significantly essential for the extensive utilization of 2D ferromagnet in magnetic racetrack memories, topological devices, and neuromorphic computing devices. The development of all‐electric functional nanodevices with multi‐state switching and a rapid reset remains challenging. Herein, to imitate the potentiation and depression process of biological synapses, a full‐current strategy is unprecedently established by the controllable resistance‐state switching originating from the spin configuration rearrangement by domain wall number modulation in Fe 3 GeTe 2 . In particular, a strong correlation is uncovered in the reduction of domain wall number with the corresponding resistance decreasing by in‐situ Lorentz transmission electron microscopy. Interestingly, the magnetic state is reversed instantly to the multi‐domain wall state under a single pulse current with a higher amplitude, attributed to the rapid thermal demagnetization by simulation. Based on the neuromorphic computing system with full‐current‐driven artificial Fe 3 GeTe 2 synapses with multi‐state switching, a high accuracy of ≈91% is achieved in the handwriting image recognition pattern. The results identify 2D ferromagnet as an intriguing candidate for future advanced neuromorphic spintronics.
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