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Advanced materials (Deerfield Beach, Fla.) · 2026

Olefin-Linked Ionic Covalent Organic Frameworks with Carbenium Backbones for High-Performance Neuromorphic Computing.

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Jiang Kaiyue, Zhou Yuhang, Wang Xiaolu, Li Dongyu, Wang Xiaowei, Lv Cunyi, Zhao Lei, Wang Hao, Zhao Jinyu, Samad Shahzeb Ali, Zhang Jichao, Cao Kecheng, Zhang Bin, Qiu Feng, Wong Wai-Yeung, Zhang Fan, Zhu Xinyuan, Zhuang Xiaodong

Аннотация

Olefin-linked covalent organic frameworks (ccCOFs) have shown great advantages in the community since discovery. However, the synthesis of ccCOFs highly relies on unsaturated heteroatom-involved segments (uSHS) to activate C─H bond to produce carbanion and to further condense with aldehydes. Such electron-withdrawing uSHS have long hindered the wide applications of ccCOFs in optoelectronic devices due to the strong electron-withdrawing effect. In this work, we report a carbenium-involved synthesis of ccCOFs without uSHS' participating. As-synthesized ionic ccCOFs show good crystallinity and ultra-narrow bandgap down to 1.03 eV without introducing complicated donor-acceptor building blocks. Such ccCOFs can also be directly synthesized as uniform films on different substrates, for example, glass, silicon wafer, Au, and so on. Most impressively, the device Au/2DPPPV-102/Al exhibits 32 distinct conductance states under low-voltage sweeps and each conductance state demonstrated excellent non-volatility and could be maintained stably for over 5000 s, which are typical features of memristor. A convolutional neural network was implemented using a 32-conductance-state memristor array and applied to image recognition, yielding recognition accuracies exceeding 90% for five randomly selected images.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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