Demonstrates enhanced recognition accuracy in neuromorphic computing using a new memory device, suggesting potential for sustainable technologies.
A flexible, eco-friendly, and photoelectrically modulated synaptic resistive random access memory (ReRAM) device has been developed using a lead-free nanoscale Cs 3 Bi 2 I 9 Quantum Dot (QD) graphene oxide (GO) composite film. The Ag/PMMA/Cs 3 Bi 2 I 9 QD/GO/ITO device exhibits a remarkable ON/OFF ratio exceeding 10 4 under illumination, representing approximately 200-fold enhancement compared to its performance in darkness (∼10 2 ). The device demonstrates exceptional mechanical and environmental stability, withstanding 10,000 bending cycles (4.6 mm radius) and 72 h of ambient exposure (25 °C, 35% RH). Furthermore, when implemented in an artificial neural network (ANN) for supervised learning, the device enables a recognition accuracy of 94.3%. We attribute this enhanced performance to a synergistic mechanism associated with the nanoscale dimension and uniform dispersion of Cs 3 Bi 2 I 9 QD in the composite. First, a poly(methyl methacrylate) (PMMA) protective layer effectively suppresses leakage current, thereby elevating the high-resistance state (HRS). Second, photogenerated holes within the Cs 3 Bi 2 I 9 QD are efficiently trapped, promoting the formation of I – vacancies (V I – ). This synergistic effect facilitates the formation of hybrid Ag/V I – conductive filaments, reducing both SET voltage (by 47.7%) and low-resistance state (LRS) resistance under illumination. These findings underscore the pivotal role of optoelectronic coupling in optimizing resistive switching behavior, paving the way for sustainable neuromorphic computing systems.
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Li et al. (2026) studied this question.
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