In Situ Growth of Metal-Organic Framework Film for Flexible Artificial Synapse

被引:7
|
作者
Lu, Qifeng [1 ]
Xia, Yizhang [2 ]
Sun, Fuqin [3 ]
Shi, Yixiang [4 ]
Zhao, Yinchao [1 ]
Wang, Shuqi [3 ]
Zhang, Ting [3 ,5 ,6 ]
机构
[1] Xian Jiaotong Liverpool Univ, XJTLU Entrepreneur Coll Taicang, Sch CHIPS, 111 Taicang Ave, Suzhou 215123, Jiangsu, Peoples R China
[2] Xiangtan Univ, Sch Comp Sci & Sch Cyberspace Sci, Xiangtan 411105, Hunan, Peoples R China
[3] Chinese Acad Sci, Suzhou Inst Nanotech & Nanob SINANO, Key Lab Multifunct Nanomat & Smart Syst, I Lab,Nano X, 398 Ruoshui Rd, Suzhou 215123, Jiangsu, Peoples R China
[4] Univ Hong Kong, Dept Chem, Pokfulam Rd, Hong Kong, Peoples R China
[5] Gusu Lab Mat, 388 Ruoshui Rd, Suzhou 215123, Jiangsu, Peoples R China
[6] Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
memristors; artificial synapses; MOFs; flexible electronics; interface quality;
D O I
10.1002/admt.202300059
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The realization of a neuromorphic system with high power efficiency and flexibility is of great significance in constructing bionic interaction systems. Although great improvement has been achieved, the systems based on hardware level remain with great challenges in device performance and stability under deformation due to the inferior interface quality. As a result, the neuromorphic systems are incompatible and incomparable with the biological ones. Therefore, an in situ growth method to synthesize the dielectric materials on flexible substrates, which can be used for the fabrication of flexible memristor-type artificial synapses, is proposed to overcome the issues. A superiority in interface quality between the synthesized Cu-3(BTC)(2) Metal-organic framework (MOF) material and the Cu foil substrate is observed benefiting from the in situ growth method, which will contribute to the improvement in device stability under deformation. In addition, the device shows continuous conductance states due to the highly accessible sites of the MOF. As a proof of concept, an artificial neural network based on the synaptic characteristics of the artificial synapse is designed, and high recognition accuracy of >80% is achieved, even with 30% allows conductance states. These results indicate that the proposed artificial synapse has great potential in the application of neuromorphic systems.
引用
收藏
页数:9
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