超晶格
磁电阻
材料科学
神经形态工程学
异质结
记忆电阻器
密度泛函理论
凝聚态物理
磁存储器
光电子学
人工神经网络
计算机科学
磁场
化学
物理
计算化学
机器学习
操作系统
量子力学
作者
Zeou Yang,Xiaozhong Huang,Yu Liu,Ze Wang,Zhengwei Zhang,Bingyang Ma,Hailong Shang,Lanzhi Wang,Zhu Tao,Xidong Duan,Hailong Hu,Jianling Yue
出处
期刊:Small methods
[Wiley]
日期:2024-12-24
卷期号:9 (5): e2401259-e2401259
被引量:4
标识
DOI:10.1002/smtd.202401259
摘要
Abstract Memristors and magnetic tunnel junctions are showing great potential in data storage and computing applications. A magnetoelectrically coupled memristor utilizing electron spin and electric field‐induced ion migration can facilitate their operation, uncover new phenomena, and expand applications. In this study, devices consisting of Pt/(LaCoO 3 /SrTiO 3 ) n /LaCoO 3 /Nb:SrTiO 3 (Pt/(LCO/STO) n /LCO/NSTO) are engineered using pulsed laser deposition to form the LCO/STO superlattice layer, with Pt and NSTO serving as the top and bottom electrodes, respectively. The results show that both memristive and magnetoresistive properties can coexist without any compromise in performance, and the values of R OFF /R ON and tunnel magnetoresistance (TMR) ratio are both improved by ≈1000% compared to a single‐period heterostructure. Notably, the Pt/(LCO/STO) 5 /LCO/NSTO device demonstrates superior multilevel storage performance, characterized by extended endurance, reliable retention, high R OFF /R ON ratio, significant TMR ratio, and fundamental synaptic behaviors. Furthermore, density functional theory (DFT) is employed to calculate the changes in oxygen vacancies, affecting the overall energy bands and magnetic moments in the monolayer and multi‐periodic structures. Simulations using the handwritten digit recognition classification achieve the highest accuracy of 94.38%. These attributes suggest that the devices hold considerable promise for application in data storage and neuromorphic computing, offering a platform for high‐density neural circuits in intelligent electronic devices.
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