Abstract
Neuromorphic computing and artificial neural networks have been developed in recent years. The oxygen vacancies in the oxide compounds have similar biological dynamics to Ca2+in brain, showing obvious advantages of compatibility with high-density cross-arrays, and are expected to achieve synaptic devices that mimic organisms. In this work, we carried out a comparative study to reveal the crucial roles played by oxygen vacancies and interface roughness, based on the non-volatile ZnO memristor. The studied system for resistive switching consists of undoped ZnO film-device sandwiched between a top and a bottom Pt electrodes, allowing the current to flow uniformly perpendicular to the film. The distribution of oxygen vacancies in the sample could be modulated by applying current. After an irreversible forming step, the I-V curve becomes hysteretic, while a threshold current produces an obvious change in the resistance. We observed different electrical rectification behaviors by using different oxygen pressures and changing the roughness of bottom Pt/ZnO interface during growth. Our investigations on the modulation of resistive switching in oxide devices are very important for the development of neural networks based on the non-volatile memory.
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