Dual-layer PMMA/CsPbBr3 regulation of Ag filament spatiotemporal dynamics in SnO2 quantum dots memristors for neuron–synapse integrated neuromorphic computing

Precise control over filament dynamics is critical for neuromorphic devices with neuronal and synaptic functions. However, most existing strategies regulate either spatial localization or temporal stability, lacking simultaneous and programmable control. Here, a dual-layer synergistic strategy is demonstrated in solution-processed SnO 2 quantum dots (QDs) memristors for programmable spatiotemporal regulation of Ag filament formation. The Br-containing CsPbBr 3 interfacial layer promotes localized Ag accumulation and modulates the spatial distribution of Ag-related conductive pathways, while PMMA regulates Ag + injection kinetics and filament evolution. By varying the PMMA thickness in Ag/(PMMA)ₙ/SnO 2 QDs/CsPbBr 3 /ITO devices, the switching behavior exhibits a PMMA-thickness-dependent evolution from nonvolatile resistive switching to volatile threshold switching. The Ag/(PMMA)ₙ =5 /SnO 2 QDs/CsPbBr 3 /ITO volatile device exhibits an operating voltage of 0.5 V, an ON/OFF ratio of 10 5 , endurance over 10 5 cycles, and leaky integrate-and-fire neuronal behavior. The Ag/(PMMA)ₙ =1 /SnO 2 QDs/CsPbBr 3 /ITO nonvolatile device shows an ON/OFF ratio of 10 3 , endurance over 10 4 cycles, and data retention exceeding 10 4 s. Based on these two modes, a hybrid neuron–synapse system is constructed, achieving 93.3% MNIST recognition accuracy. This work provides a programmable filament dynamics paradigm for scalable neuromorphic computing hardware.