ZnO-based resistive memory with self-rectifying behavior for neuromorphic devices

Resistive random-access memory (RRAM) is a type of next-generation low-energy memory used in artificial intelligence by controlling the high- and low-resistance states. By the migration of oxygen vacancies, two states are controlled. ITO/ZnO/TaN is proposed as a nonvolatile memory RRAM device. Additionally, the interface layer between the ITO and ZnO layer is shown by transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS), which results in rectifying characteristics. The device exhibits bipolar resistive switching and a gradual I-V curve through DC voltage sweep cycling after the electroforming procedure, implying the potential for neuromorphic systems. Furthermore, the device's synaptic behaviors are proved, including potentiation and depression, spike-amplitude-dependent plasticity, spike-number-dependent plasticity, spike-duration-dependent plasticity, and spike-timing-dependent plasticity suitability. Furthermore, ISPVA was utilized for better endurance, potentiation and depression, and MLC retention.