ScholarWorks@성균관대학교

초록

Visual perception in biological systems relies on integrated sensory reception and synaptic processing, enabling adaptive and energy-efficient interpretation of optical stimuli. Inspired by these principles, artificial optical synapses that combine optical sensing with memory functions have emerged as key components for neuromorphic vision systems. In this study, a flexible artificial optical sensory synapse (A-OSS) based on an ionogel (IG)-gated field-effect transistor, featuring a heterojunction channel composed of reduced graphene oxide and vertically aligned ZnO nanorods is presented. Under pulsed ultraviolet illumination, the device exhibits a strong photo-gating effect that modulates channel conductance and induces pronounced optical synaptic plasticity. The IG gate-dielectric, composed of a polyurethane matrix embedded with the ionic liquid [EMIM][TFSI], enhances synaptic response and retention via increased interfacial capacitance and delayed ionic relaxation dynamics. The A-OSS encodes pulsed light signals into distinct post-synaptic current (PSC) patterns, which are effectively decoded through machine learning algorithms for accurate symbolic information recognition. It is demonstrated high-accuracy decoding of digits and letters, represented using Morse and ASCII schemes, through synaptic strength variations derived from PSC decay profiles. This work highlights a light-responsive, mechanically flexible, and low-power platform for advanced neuromorphic vision and intelligent sensing applications.

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