Zhao Zhizheng, El-Khouly Mohamed E, Che Qiang, Sun Fangcheng, Zhang Bin, He Haidong, Chen Yu
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.
Institute of Basic and Applied Sciences, Egypt-Japan University of Science and Technology (E-JUST), Alexandria, 21934, Egypt.
Angew Chem Int Ed Engl. 2023 Feb 6;62(7):e202217249. doi: 10.1002/anie.202217249. Epub 2023 Jan 10.
As a conjugated and unsymmetric building block composed of an electron-poor seven-membered sp 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.
作为一种由缺电子的七元sp碳环和富电子的五元碳环组成的共轭且不对称的结构单元,薁及其衍生物因其固有的氧化还原活性而被认为是新型电子器件最有前途的结构单元之一。首次以1,3,5-三(4-氨基苯基)苯和薁-1,3-二甲醛为原料,通过液-液界面聚合策略制备了一种基于薁(Azu)的二维共轭共价有机框架COF-Azu。制备的Al/COF-Azu/氧化铟锡(ITO)忆阻器由于电场诱导的分子内电荷转移效应而表现出典型的非易失性电阻开关性能。结合独特的忆阻性能,构建了一个简单的卷积神经网络用于图像识别。经过8个训练周期后,在更大数据集上训练的神经网络实现了80%的图像识别准确率。