ScholarWorks@중앙대학교

초록

Next-generation neuromorphic systems require hardware platforms that seamlessly integrate sensing, memory, and computation. Here, we present a light-programmable optoelectronic memristor based on an ITO/IGZO/W structure, capable of emulating a broad spectrum of synaptic and neuronal functions under purely optical stimulation through the transparent ITO top electrode. The device exhibits short-term plasticity, including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and spike-dependent learning behaviors (SADP, SWDP, SNDP). It also replicates nociceptive responses such as threshold activation, no adaptation, relaxation, and sensitization. Pavlovian associative learning is demonstrated using optical stimuli, showing acquisition, extinction, and recovery behaviors driven by persistent photoconductivity. Furthermore, a 4-bit optical pulse-driven reservoir computing architecture achieves 97.005% MNIST classification accuracy through a convolutional neural network readout. A light-induced stochastic activation function, extracted from threshold-switching behavior, is applied in a Restricted Boltzmann Machine to model probabilistic neurons, reaching 96.35% image reconstruction accuracy. Postforming optical modulation enables light-intensity-dependent trap/detrap dynamics and fine-tuning of the conductive filament. These results highlight the proposed IGZO-based optoelectronic memristor as a versatile and energy-efficient platform for multifunctional neuromorphic computing, combining sensory, deterministic, and probabilistic intelligence in a single reconfigurable device.

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