Regulating WORM/Flash electrical memory behavior of metallopolymers through varying metal centers

1 We reported the facile regulation of memory behavior of metallopolymers by varying the central metal ions. 2 The inserted Co and Ni ions in the porphyrin moieties of metallopolymers can enhance the intramolecular or intermolecular charge transfer (CT) and back charge transfer (CT) effect. 3 The logic gates and information display function based on NiPt-containing device have been successfully accomplished. To study the influence of metal atoms on the performance of organic polymer memory devices, four new metallopolymers P0, P1, P2 and P3 were designed and synthesized for organic resistive random-access memory (RRAM) applications. Among them, the device based on P1 shows nonvolatile binary write-once-read-many-times (WORM) memory behavior, while the devices based on P2 and P3 show vastly different nonvolatile binary Flash-type memory behavior. The charge transfer (CT) effect between the platinum (Pt) ligand and porphyrin moieties of metallopolymers is determined to be the origin of the electrical switching behavior of P1 , which is proved by the electrochemical and DFT calculations. While the reason of the Flash type memory characteristic of P2 and P3 is ascribed to the formation of metal filaments because of the introduction of metal ions (Co and Ni) into the porphyrin ring. It is suggested that the metal ions can form an internal electrode and act as a bridge during the CT process, which contributes to both the CT and back CT, consequently regulating the WORM/Flash conversion. The results indicate the feasibility of modulating the memory behavior of metallopolymers by varying the central metal ions, manifesting the significance of metal complexes in the application of organic memory devices and will attract wide research interest of scientists. The as-fabricated device based on P3 was also successfully applied to memory logic gates and display function, which offers great application prospect as smart sensor in artificial intelligence (AI) network.