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Towards High-Performance Resistive Switching Behavior through Embedding a D-A System into 2D Imine-Linked Covalent Organic Frameworks.

Chenyu LiDong LiWeifeng ZhangHao LiGui Yu
Published in: Angewandte Chemie (International ed. in English) (2021)
Developing new materials for the fabrication of resistive random-access memory is of great significance in this period of big data. Herein, we present a novel design strategy of embedding donor (D) and acceptor (A) fragments into imine-linked frameworks to construct resistive switching covalent organic frameworks (COFs) for high-performance memristors. Two D-A-type two-dimensional COFs, COF-BT-TT and COF-TT-TVT, were designed and synthesized using a conventional solvothermal approach, and high-quality thin films of these materials deposited on ITO substrate exhibited great potential as an active layer for memristors. Rewritable memristors based on 100 nm thick COF-TT-BT and COF-TT-TVT films showed a high ON/OFF current ratio (ca. 105 and 104 ) and low driving voltage (1.30 and 1.60 V). The cycle period and retention time for COF-TT-BT-based rewritable devices were as high as 319 cycles and 3.3×104  s at a constant voltage of 0.1 V (160 cycles and 1.2×104  s for the COF-TT-TVT memristor).
Keyphrases
  • big data
  • artificial intelligence
  • machine learning
  • deep learning
  • climate change
  • room temperature
  • water soluble