记忆电阻器
神经形态工程学
电导
材料科学
蛋白质丝
纳米技术
电流密度
Atom(片上系统)
电极
光电子学
可扩展性
化学物理
电子工程
人工神经网络
凝聚态物理
计算机科学
化学
物理
复合材料
量子力学
数据库
机器学习
工程类
物理化学
嵌入式系统
作者
Chenyu Zhuge,Yukun Zhang,Jiandong Jiang,Xiang Li,Yanfei Zhao,Yujun Fu,Qi Wang,Deyan He
出处
期刊:Small
[Wiley]
日期:2024-06-11
标识
DOI:10.1002/smll.202400599
摘要
Abstract Memristors are used in artificial neural networks owing to their exceptional integration capabilities and scalability. However, traditional memristors are hampered by limited resistance states and randomness, which curtails their application. The migration of metal ions critically influences the number of conductance states and the linearity of weight updates. Semi‐metal filaments can provide subquantum conductance changes to the memristors due to the smaller single‐atom conductance, such as Sb (≈0.01 G 0 = 7.69 × 10 −7 S). Here, a memristor featuring an active electrode composed of semi‐metal Sb is introduced for the first time. This memristor demonstrates precise conductance control, a large on/off ratio, consistent switching, and prolonged retention exceeding 10 5 s. Density functional theory (DFT) calculations and characterization methods reveal the formation of Sb filaments during a set process. The interaction between Sb and O within the dielectric layer facilitates the Sb filaments' ability to preserve their morphology in the absence of electric fields.
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