神经形态工程学
材料科学
接口(物质)
突触
铁电性
领域(数学分析)
光电子学
纳米技术
复合材料
神经科学
人工神经网络
计算机科学
人工智能
数学分析
数学
毛细管数
毛细管作用
电介质
生物
作者
Xiaoqi Li,Jiaqi Liu,Fan Xu,Sajjad Ali,Han‐Chieh Wu,Biaohong Huang,Haoyue Deng,Yizhuo Li,Yuxuan Jiang,Zhen Fan,Yun‐Long Tang,Yujia Wang,M. Bououdina,Teng Yang,Weijin Hu,Zhidong Zhang
标识
DOI:10.1002/adfm.202423225
摘要
Abstract Ferroelectric (FE) synapses are promising for neuromorphic computing toward enhanced artificial intelligence systems. Nonetheless, there is a significant gap in understanding how to effectively tailor self‐polarization and its implications on synaptic device performance. Here, an approach using interfacial element accumulation is reported to tailor the self‐polarization states of BaTiO 3 (BTO)/La 0.67 Sr 0.33 MnO 3 (LSMO) FE heterostructure into a single domain state. This single domain configuration results are demonstrated in a gradient distribution of oxygen vacancies across the film thickness, yielding an extraordinary on/off ratio of 10 7 in Pt/BTO/LSMO FE diodes. This giant resistive switching enables the long‐term potentiation and long‐term depression synaptic functions of excellent linearity and symmetry (with a nonsymmetry factor as low as 0.1), leading to a supervised learning ability of the associated artificial neural network with a high pattern recognition accuracy of 95%. This work provides a simple design principle for FE single domain, which is substantial in enhancing the performance of FE synapses for neuromorphic computing.
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