The advancement of edge neuromorphic computing hinges on developing memory devices that combine high integration density with intelligent functionality. However, high-density crossbar arrays, a conventional architecture for such systems, are often plagued by inherent sneak-path currents. Furthermore, achieving multifunctional integration of analog and digital bipolar resistive switching (RS) within a single device remains a significant challenge. Here, we report a quasi-digital memristor (QDM) based on an Ag/AgI/PbI2/ITO architecture, which integrates tri-functional attributes: diode-like rectification, digital switching, and analog synaptic modulation. High self-rectifying ratio and selectivity are achieved through the strategic design of a p-n junction at the AgI/PbI2 Interface. The switching mechanism is governed by the field-driven migration of dopant ions (e.g., Ag+, iodine vacancies) within the functional layers. In the analog mode, a synaptic array constructed from QDMs demonstrates a recognition accuracy of 97.2% for 8 × 8-pixel letter images (A–Z) after only six training epochs. In the digital mode, the QDM exhibits a high ON/OFF ratio, robust data retention, and excellent cycling endurance. Notably, the device also features a record-low set voltage, enabling superior system-level energy efficiency. This work presents a novel and effective pathway toward precise, high-density information processing in neuromorphic computing systems.
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