Synergistic enhancement of memristive behavior and self-rectifying effect in MnO₂ based memristor by ions doping method

As one of the most promising candidates to replace the traditional von Neumann architecture, memristor shows considerable potential in neuromorphic computing, neural networks, brain-like chips, artificial intelligence, and information storage. However, its performance in terms of ultra-high stability, scalability, and extended switching windows has yet to be broken through, limiting its practical applications. In this work, it is investigated in detail the effect of Cu²⁺/Zn²⁺ ions doping on the memristive performance in the Ag/δ-MnO₂/Ti devices with three different doping concentrations. We found that the optimal doping concentration can significantly improve the stability and resistance switching ratio of the device. Through first principles analysis, it is further confirmed that the main mechanism for the improvement in device switching ratio is the reduction of MnO bandgap caused by Cu²⁺/Zn²⁺ ions doping. Finally, we proposed that the formation of CuO/ZnO buffer layer through the interaction between Cu²⁺/Zn²⁺ ions and O^2- ions is the key factor leading to the transition of threshold voltage from self-rectification to memristive behavior. Therefore, this work provides an in-deep understanding of the theory of metal ions doping in memristive device, which adds a new strategy to improve the memristive performance of the device in neuromorphic applications.