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Redox-Active Azulene-based 2D Conjugated Covalent Organic Framework for Organic Memristors |
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| Authors: | Zhizheng Zhao Prof Mohamed E El-Khouly Qiang Che Fangcheng Sun Dr Bin Zhang Prof Haidong He Prof Yu Chen |
| Institution: | 1. Key Laboratory for Advanced Materials and Joint International Research Laboratory of Precision Chemistry and Molecular Engineering, Feringa Nobel Prize Scientist Joint Research Center, School of Chemistry and Molecular Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237 China
Contribution: ?Investigation (equal);2. Institute of Basic and Applied Sciences, Egypt-Japan University of Science and Technology (E-JUST), Alexandria, 21934 Egypt Contribution: ?Investigation (equal);3. Key Laboratory for Advanced Materials and Joint International Research Laboratory of Precision Chemistry and Molecular Engineering, Feringa Nobel Prize Scientist Joint Research Center, School of Chemistry and Molecular Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237 China;4. Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199 China |
| Abstract: | As a conjugated and unsymmetric building block composed of an electron-poor seven-membered sp2 carbon ring and an electron-rich five-membered carbon ring, azulene and its derivatives have been recognized as one of the most promising building blocks for novel electronic devices due to its intrinsic redox activity. By using 1,3,5-tris(4-aminophenyl)-benzene and azulene-1,3-dicarbaldehyde as the starting materials, an azulene(Azu)-based 2D conjugated covalent organic framework, COF-Azu, is prepared through liquid-liquid interface polymerization strategy for the first time. The as-fabricated Al/COF-Azu/indium tin oxide (ITO) memristor shows typical non-volatile resistive switching performance due to the electric filed induced intramolecular charge transfer effect. Associated with the unique memristive performance, a simple convolutional neural network is built for image recognition. After 8 epochs of training, image recognition accuracy of 80 % for a neutral network trained on a larger data set is achieved. |
| Keywords: | Azulene Covalent Organic Framework Image Recognition Materials Synthesis Organic Memristors |