Defect-Driven Neuromorphic Plasticity in Planar ZnO Optoelectronic Synapses

Understanding how atomic-scale defect dynamics influence system-level neuromorphic behavior is crucial for the rational design of oxide-based optoelectronic synapses. In this study, a planar ZnO synapse has been introduced where the nanosecond-scale oxygen-vacancy carrier lifetime is directly linked to second-scale persistent photoconductivity (PPC) decay and key synaptic plasticity parameters. By combining steady-state and time-resolved spectroscopies with electrical measurements, a dynamic framework that spans multiple time scales has been developed: long-lived defect states slow PPC decay, which in turn regulates paired-pulse facilitation retention and the efficiency of short-to-long-term plasticity transitions. This framework allows for predictive tuning of the synaptic weight by controlling defect occupation and release kinetics. The optimized ZnO synapse operating at 0.1 V demonstrates robust long-term potentiation and achieves 90.8% recognition accuracy in handwritten digit recognition. This work presents a cross-time scale design strategy that bridges atomic-level defect engineering with neuromorphic system performance, paving a route toward artificial vision hardware.