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

Author:

Lu Qifeng1ORCID,Xia Yizhang2,Sun Fuqin3,Shi Yixiang4,Zhao Yinchao1,Wang Shuqi3,Zhang Ting356ORCID

Affiliation:

1. School of CHIPS XJTLU Entrepreneur College (Taicang) Xi'an Jiaotong‐Liverpool University 111 Taicang Avenue, Taicang Suzhou Jiangsu 215123 P. R. China

2. School of Computer Science & School of Cyberspace Science Xiangtan University Yuhu District Xiangtan Hunan 411105 P. R. China

3. i‐lab Key Laboratory of Multifunctional Nanomaterials and Smart Systems Nano‐X Suzhou Institute of Nano‐Tech and Nano‐Bionics (SINANO) Chinese Academy of Sciences (CAS) 398 Ruoshui Road Suzhou Jiangsu 215123 P. R. China

4. Department of Chemistry The University of Hong Kong Pokfulam Road Hong Kong P. R. China

5. Gusu Laboratory of Materials 388 Ruoshui Road Suzhou Jiangsu 215123 P. R. China

6. Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai 200031 P. R. China

Abstract

AbstractThe 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 Cu3(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.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

Wiley

Subject

Industrial and Manufacturing Engineering,Mechanics of Materials,General Materials Science

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